.e SJ-11-3 @net: sj 11-3 st0231!st0231@
.c sj
.a N. Orsini and M. Bottai
.t Logistic quantile regression in Stata
.k stat-istics lqreg lqregpred lqregplot logis-tic reg-ressions quantile-s
.k robust bound-ed bound-s outcome-s est-imation est-imates pred-ictions
.k graph-s graph-ing graph-ics
.x
	(@lqreg@, @lqreg_postestimation@, @lqregpred@, @lqregplot@ if installed)
	Q3/11	@browser:http://www.stata-journal.com/article.html?article=st0231!SJ 11(3):327--344@
	estimation, prediction, and graphical representation of
	logistic quantile regression

.e SJ-11-3 @net: sj 11-3 st0232!st0232@
.c sj
.a T. M. Palmer, R. R. Ramsahai, V. Didelez, and N. A. Sheehan
.t Nonparametric bounds for causal effects in a binary IV model
.k stat-istics bpbounds bpboundsi nonpar-ametric bound-s
.k ave-rages caus-al effect-s
.k bina-ry instrum-ental var-iables infer-ence ratio-s risk-s
.x
	(@bpbounds@, @bpboundsi@ if installed)
	Q3/11	@browser:http://www.stata-journal.com/article.html?article=st0232!SJ 11(3):345--367@
	calculates the nonparametric bounds for the intervention
	probabilities and average causal effect in a binary
	instrumental-variable model

.e SJ-11-3 @net: sj 11-3 st0233!st0233@
.c sj
.a M. Lokshin and Z. Sajaia
.t Impact of interventions on discrete outcomes
.k stat-istics switch_probit switch_probit_d2 switch_probit_p
.k discrete outcome-s max-imum like-lihood
.k est-imation bina-ry choice model-s endog-enous reg-ressors endog-enous
.k var-iables limit-ed depend-ent impact evaluation-s marginal treat-ments
.k effect-s param-eters
.o @switch_probit@ if installed
.x
	Q3/11	@browser:http://www.stata-journal.com/article.html?article=st0233!SJ 11(3):368--385@
	implements the maximum likelihood method to fit the model
	of the binary choice with binary endogenous regressors

.e SJ-11-3 st0234
.c sj
.a M. P. Caria, R. Bellocco, M. R. Galanti, and N. J. Horton
.t An application of multiple-source information models
.k stat-istics model-s mult-iple source reg-ressions based method-s
.k data pred-ictors anal-ysis general-ized estimat-ing equation-s
.k miss-ing
.x
	Q3/11	@browser:http://www.stata-journal.com/article.html?article=st0234!SJ 11(3):386--402@				    (no commands)
	describes regression-based methods for analyzing
	multiple-source data in Stata; example combines two
	measures of body mass index and relates them to smoking
	onset

.e SJ-11-3 st0235
.c sj
.a D. A. Wagstaff and O. Harel
.t Small-sample approx. to multiple-imputation deg. of freedom
.k stat-istics miss-ing data mult-iple imput-ation small samp-les
.k degree-s freedom chain-ed equation-s multiv-ariate norm-al
.k ice mvn
.x
	Q3/11	@browser:http://www.stata-journal.com/article.html?article=st0235!SJ 11(3):403--419@				    (no commands)
	simulation comparison of three small-sample approximations
	to the degrees of freedom for multiple imputation of a
	continuous predictor using chained equation or multivariate
	normal imputation

.e SJ-11-3 @net: sj 11-3 st0236!st0236@
.c sj
.a U. Kohler, K. B. Karlson, and A. Holm
.t Comparing coef. of nested nonlinear probability models
.k stat-istics khb lkhb compar-e coef-ficients nest-ed nonlin-ear prob-ability
.k model-s decomp-osition karlson holm breen path-s anal-ysis
.k total-s effect-s indirect logit probit primary effect-s general-ized
.k linear model-s
.o @khb@ if installed
.x
	Q3/11	@browser:http://www.stata-journal.com/article.html?article=st0236!SJ 11(3):420--438@
	implements the Karlson, Holm, and Breen (KHB) method for
	comparing the estimated coefficients of two nested
	nonlinear probability models

.e SJ-11-3 @net: sj 11-3 st0237!st0237@
.c sj
.a A. Doris, D. O'Neill, and O. Sweetman
.t GMM est. of the covariance structure of longitudinal data
.k stat-istics gmmcovearn nlgmmcovearn
.k general-ized method-s mom-ents gmm est-imation
.k cov-ariances structure longi-tudinal data earnings permanent
.k inequal-ity transitory
.o @gmmcovearn@ if installed
.x
	Q3/11	@browser:http://www.stata-journal.com/article.html?article=st0237!SJ 11(3):439--459@
	provides generalized method of moments estimation of the
	covariance structure of longitudinal data on earnings

.e SJ-11-3 dm0058
.c sj
.a N. J. Cox
.t Speaking Stata: Fun and fluency with functions
.k data-sets set-s manage-ment func-tions num-erical str-ings
.x
	Q3/11	@browser:http://www.stata-journal.com/article.html?article=dm0058!SJ 11(3):460--471@				    (no commands)
	a tour of easily missed or underestimated Stata functions

.e SJ-11-3 dm0059
.c sj
.a N. J. Cox
.t Stata tip 101: Previous but different
.k data-sets set-s manage-ment tip value previous time-series series _n
.x
	Q3/11	@browser:http://www.stata-journal.com/article.html?article=dm0059!SJ 11(3):472--473@				    (no commands)
	illustrates indentifying the most recent value that differed
	from the present value in an irregularly spaced time series

.e SJ-11-3 @net:sj 11-3 gr0049!gr0049@
.c sj
.a N. J. Cox
.t Stata tip 102: Highlighting specific bars
.k graph-s graph-ing graph-ics tip highlight-ing bar-s dot-s chart-s keep
.k sort order bartip
.x
	Q3/11	@browser:http://www.stata-journal.com/article.html?article=gr0049!SJ 11(3):474--477@
	tip on highlighting a subset of observations in a bar or
	dot chart

.e SJ-11-3 @net:sj 11-3 st0049_1!st0049_1@
.c sj
.a J. W. Hardin, R. J. Carroll, and H. Schmiediche
.t Instrumental variables, bootstrapping, and gen. lin. models
.k reg-ressions fit-ted fit-s meas-urements meas-ures calibra-tion
.k instrum-ental var-iables repli-cates matr-ices matr-ix
.k err-ors boot-strapped miss-ing cov-ariances covariate-s
.k stat-istics stand-ard general-ized linear mod-els glm rcal _crcdeq qvfmex
.x
	(@rcal@ if installed)
	Q3/11	@browser:http://www.stata-journal.com/article.html?article=up0033!SJ 11(3):478@
	bug fix for ^rcal^

.e SJ-11-3 @net: sj 11-3 st0215_1!st0215_1@
.c sj
.a N. Orsini and S. Greenland
.t Tab. and plot results after flex. modeling of quant. cov.
.k stat-istics xblc tab-ulate tab-ulations plot-s graph-s graph-ing graph-ics
.k result-s flexible model-s model-ing quantile-s covariate-s response-s
.k var-iables reg-ressions coef-ficients cub-ic spline-s interv-als
.k p value-s lincom linear pred-ictions
.o @xblc@ if installed
.x
	Q3/11	@browser:http://www.stata-journal.com/article.html?article=up0033!SJ 11(3):478@
	bug fix and added graph options for ^xblc^

.e SJ-11-2 gn0051
.c sj
.a C. F. Baum
.t Richard Sperling (1961-2011)
.k richard sperling obituary
.x
	Q2/11	@browser:http://www.stata-journal.com/article.html?article=gn0051!SJ 11(2):157--158@				    (no commands)
	obituary

.e SJ-11-2 @net: sj 11-2 st0224!st0224@
.c sj
.a D. Roodman
.t Fitting fully observed recursive mixed-process models
.k stat-istics cmp ghk2 geweke hajivassiliou keane algor-ithms recurs-ive
.k mixed process-es model-s seemingly unrel-ated reg-ressions probit mata
.k liml fiml instrum-ental var-iables system-s simult-aneous eq-uations
.k ivprobit piprobit treatreg oprobit mprobit asmprobit tobit ivtobit cnreg
.k intreg truncreg heckman heckprob tetrachoric
.k ghk ghkfast cmp_clear cmp_d2 cmp_lf cmp_p ghk2version
.o @cmp@, @ghk2@ if installed
.x
	Q2/11	@browser:http://www.stata-journal.com/article.html?article=st0224!SJ 11(2):159--206@
	fits simultaneous-equation fully observed recursive
	mixed-process models

.e SJ-11-2 @net: sj 11-2 st0225!st0225@
.c sj
.a J. M. C. Santos Silva and S. Tenreyro
.t @poisson@: Some convergence issues
.k stat-istics ppml poisson reg-ressions collinear-ity numer-ical problem-s
.k perfect pred-ictions est-imates exist-ence check-s converg-ence
.o @ppml@ if installed
.x
	Q2/11	@browser:http://www.stata-journal.com/article.html?article=st0225!SJ 11(2):207--212@
	provides improved Poisson regression by checking for the
	existence of the estimates and providing two methods for
	dropping regressors that cause nonexistence of estimates

.e SJ-11-2 @net: sj 11-2 st0226!st0226@
.c sj
.a G. De Luca and V. Perotti
.t Estimation of ordered response models with sample selection
.k stat-istics opsel post-estimations sneop snp2 snp2s snpopsel snp order-ed
.k response-s model-s samp-les selec-tion est-imation max-imum like-lihood
.k param-etric nonpar-ametric semi-nonparametric bivar-iate gauss-ian
.k distrib-utions gallant nychka fit dens-ity func-tions err-ors
.k approx-imations hermite poly-nomials expan-sion
.k dropping opsel_ll opsel_p sneop_ll sneop_p snp2_ll snp2_p snp2s_ll snp2s_p
.k snp_ll snp_p snpopsel_ll snpopsel_p
.x
	(@opsel@, @snpopsel@, @sneop@, @snp@, @snp2@, @snp2s@ if installed)
	Q2/11	@browser:http://www.stata-journal.com/article.html?article=st0226!SJ 11(2):213--239@
	provides parametric and semi-nonparametric estimation of
	ordered response models with sample selection

.e SJ-11-2 @net: sj 11-2 st0227!st0227@
.c sj
.a C. U. Kunz and M. Kieser
.t Simon's & Jung's two-stage designs with/without curtailment
.k stat-istics simontwostage simon jung two stage design-s admissible
.k phase trial-s cond-itional power curtailment critical value-s sample-s
.k size oncology stochastic nonstochastic rule-s
.o @simontwostage@ if installed
.x
	Q2/11	@browser:http://www.stata-journal.com/article.html?article=st0227!SJ 11(2):240--254@
	calculates critical values and sample sizes for two-stage
	designs for phase II oncology trials

.e SJ-11-2 @net: sj 11-2 st0156_1!st0156_1@
.c sj
.a I. R. White
.t Multivariate random-effects meta-regression: Updates
.k stat-istics multiv-ariate rand-om effect-s meta anal-ysis param-eters
.k mult-iple outcome-s compar-isons compar-e group-s mvmeta mvmeta_l max-imum
.k like-lihood restric-ted restric-tions method-s of mom-ents est-imates
.k est-imation model-s mvmeta_make ml-e reml metareg newton-raphson raphson
.k synt-ax opt-ions nota-tion variance-s sav-ed result-s between study studies
.k covariate-s cov-ariances util-ity univar-iate heterog-eneity perfect
.k pred-ictions separ-ate reg-ressions augment-ed matr-ix matr-ices
.k mvmeta_bscov_correlation mvmeta_bscov_equals mvmeta_bscov_proportional
.k mvmeta_bscov_unstructured mvmeta_lmata mvmeta_mufromsigma
.o @mvmeta@, @mvmeta_make@ if installed
.x
	Q2/11	@browser:http://www.stata-journal.com/article.html?article=st0156_1!SJ 11(2):255--270@
	extension of ^mvmeta^ command to handle meta-regression

.e SJ-11-2 @net: sj 11-2 st0228!st0228@
.c sj
.a P. Tebaldi, M. Bonetti, and M. Pagano
.t M stat. commands: Interpoint distance distribution analysis
.k stat-istics mstat mtest m spmap interpoint distance-s monte carlo test-s
.k anal-ysis distrib-utions across group-s obs-ervations spatial
.k diff-erences permu-tation graph-ical
.k dbins _diff diff_iter eucldist fhat mst_iter smat
.x
	(@mstat@, @mtest@ if installed)
	Q2/11	@browser:http://www.stata-journal.com/article.html?article=st0228!SJ 11(2):271--289@
	compares the interpoint distance distribution across groups
	of observations

.e SJ-11-2 st0162_1
.c sj
.a P. Cummings
.t Estimating adjusted risk ratios for matched/unmatched data
.k stat-istics est-imates est-imation meth-ods adjust-ed risk-s ratio-s
.k mantel-haenszel haenszel inv-erse variance-s general-ized linear
.k reg-ressions case-control control-s odds outcome-s incid-ence irr-s
.k logis-tic cond-itional clogit adjust-ed expos-ures expos-ed pop-ulations
.k conf-idence interv-als strat-ified log-s link-ed binom-ial distrib-utions
.k converg-ence robust est-imators glm poisson std err-ors stand-ard cox
.k propor-tional haz-ards stand-ardization stand-ardized stand-ardisation
.k stand-ardised substitut-ion boot-strapped match-ed unmatch-ed
.k xtpoisson fe margin-s cohort
.x
	Q2/11	@browser:http://www.stata-journal.com/article.html?article=st0162_1!SJ 11(2):290--298@				      (no commands)
	shows how the @margins@ command and the robust variance
	option (^vce(robust)^) for conditional Poisson regression
	(@xtpoisson@^, fe^) make it easier to estimate adjusted
	risk ratios

.e SJ-11-2 @net: sj 11-2 st0229!st0229@
.c sj
.a K. Lukacsy
.t Generating random samples from user-defined distributions
.k stat-istics rsample rand-om samp-les gen-erate distrib-utions func-tions
.o @rsample@ if installed
.x
	Q2/11	@browser:http://www.stata-journal.com/article.html?article=st0229!SJ 11(2):299--304@
	generates a random sample from any user-specified distribution
	function

.e SJ-11-2 dm0055
.c sj
.a N. J. Cox
.t Speaking Stata: Compared with ...
.k data-sets set-s manage-ment panel-s subsc-ripting summ-arize
.k by sum cond logic-al expr-essions egen tag sort
.x
	Q2/11	@browser:http://www.stata-journal.com/article.html?article=dm0055!SJ 11(2):305--314@				    (no commands)
	reviews techniques for relating values to values in other
	observations

.e SJ-11-2 st0230
.c sj
.a M. L. Buis
.t Stata tip 97: Getting at rho's and sigma's
.k stat-istics tip rho sigma est-imates coef-ficients param-eters test-s
.k hyp-otheses constrain-ts transfo-rmed
.x
	Q2/11	@browser:http://www.stata-journal.com/article.html?article=st0230!SJ 11(2):315--317@				     (no commands)
	tip on how to access, test hypotheses, and impose
	constraints on transformed parameters of a model

.e SJ-11-2 dm0056
.c sj
.a N. J. Cox
.t Stata tip 98: Counting substrings within strings
.k data-sets set-s manage-ment tip count-ing substr-ings str-ings subinstr
.k sdate length
.x
	Q2/11	@browser:http://www.stata-journal.com/article.html?article=dm0056!SJ 11(2):318--320@				    (no commands)
	tip on counting substrings within strings

.e SJ-11-2 dm0057
.c sj
.a C. Schechter
.t Stata tip 99: Taking extra care with @encode@
.k data-sets set-s manage-ment tip encode distinct map-ping str-ings var-iables
.k inte-gers value-s numer-ical append merge label-s
.x
	Q2/11	@browser:http://www.stata-journal.com/article.html?article=dm0057!SJ 11(2):321--322@				    (no commands)
	tip on safely using ^encode^ across datasets

.e SJ-11-2 pr0052
.c sj
.a W. Gould and N. J. Cox
.t Stata tip 100: Mata and the case of the missing macros
.k prog-ramming prog-rams tip mata miss-ing macro-s local-ly global-ly
.k substitut-ion
.x
	Q2/11	@browser:http://www.stata-journal.com/article.html?article=pr0052!SJ 11(2):323--324@				    (no commands)
	tip showing how to do the equivalent of Stata's macro
	substitution in Mata

.e SJ-11-2 @net: sj 11-2 st0171_1!st0171_1@
.c sj
.a K. Finlay and L. M. Magnusson
.t Software update for ^rivtest^
.k stat-istics weak instrum-ental robust test-s test-ing general-ized class
.k var-iables model-s rivtest est-imates est-imation estimat-ing conf-idence
.k interv-als endog-enous hyp-othesis hyp-otheses est-imators linear tobit
.k probit ivtobit ivprobit limit-s limited depend-ent ldv homosce-dasticity
.k homoske-dasticity post-estimations anderson rubin-s overident-ification
.k condivreg ivreg2 min-imums distance-s resid-uals
.k hetero-scedasticity hetero-skedasticity clus-tered depend-ence iv-regress
.k variance-s joint two-stage stage 2 least
.k sq-uares exog-enous monte carlo simul-ations
.o @rivtest@ if installed
.x
	Q2/11	@browser:http://www.stata-journal.com/article.html?article=up0032!SJ 11(2):325@
	updated to support factor variables; errors fixed

.e SJ-11-1 @net: sj 11-1 st0215!st0215@
.c sj
.a N. Orsini and S. Greenland
.t Tabulate and plot results after flex. modeling of quant. cov.
.k stat-istics xblc tab-ulate tab-ulations plot-s graph-s graph-ing graph-ics
.k result-s flexible model-s model-ing quantile-s covariate-s response-s
.k var-iables reg-ressions coef-ficients cub-ic spline-s interv-als
.k p value-s lincom linear pred-ictions
.o @xblc@ if installed
.x
	Q1/11	@browser:http://www.stata-journal.com/article.html?article=st0215!SJ 11(1):1--29@
	provides a postestimation command that facilitates the
	presentation of the association between a quantitative
	covariate and the response variable

.e SJ-11-1 @net: sj 11-1 st0216!st0216@
.c sj
.a J.-B. Hardouin, A. Bonnaud-Antignac, and V. Sebille
.t Nonparametric item response theory using Stata
.k stat-istics anaoption gengroup genscore guttmax loevh msp traceline-s item-s
.k response-s theory bina-ry ordinal model-s var-iables latent mokken scale-s
.k graph-s graph-ing graph-ics plot-s trace scat-terplots guttman error-s
.k loevinger-s h irt
.x
	(help @gengroup@, @loevh@, @msp@, @tracelines@ if installed)
	Q1/11	@browser:http://www.stata-journal.com/article.html?article=st0216!SJ 11(1):30--51@
	provides commands for nonparametric item response theory

.e SJ-11-1 @net: sj 11-1 gr0048!gr0048@
.c sj
.a R. Corten
.t Visualization of social networks using multidim. scaling
.k stat-istics network-s data-sets set
.k multi-dimensional dimen-sional dim-ensions scale-d
.k scaling mds netplot graph-s graph-ing graph-ics visual social anal-ysis
.k patt-erns interact-ions visualization bina-ry draw-s plot-s
.o @netplot@ if installed
.x
	Q1/11	@browser:http://www.stata-journal.com/article.html?article=gr0048!SJ11(1):52--63@
	provides multidimensional scalaing methods for visualizing
	social networks

.e SJ-11-1 @net: sj 11-1 st0217!st0217@
.c sj
.a M. Cefalu
.t Pointwise conf. inter. for cov.-adjusted survivor function
.k stat-istics survci survci_10 pointwise conf-idence interv-als covariate-s
.k adjust-ed surviv-al func-tions cox model-s graph-s graph-ing graph-ics
.k surviv-al func-tions cumul-ative haz-ards stcox cancer-.dta
.o @survci@, @survci_10@ if installed
.x
	Q1/11	@browser:http://www.stata-journal.com/article.html?article=st0217!SJ11(1):64--81@
	plots pointwise confidence intervals for the survivor
	function after the Cox model

.e SJ-11-1 @net: sj 11-1 st0218!st0218@
.c sj
.a H. Farbmacher
.t Estimation of hurdle models for overdispersed count data
.k stat-istics ztpnm est-imates est-imation est-imators hurdle model-s
.k count-s data-sets set-s zero trunc-ated poisson log-normal norm-al
.k distrib-utions anal-ysis over-dispersion bina-ry logit probit gauss hermite
.k mc_ztpnm ztpnm_ada_ll ztpnm_ll
.o @ztpnm@ if installed
.x
	Q1/11	@browser:http://www.stata-journal.com/article.html?article=st0218!SJ11(1):82--94@
	estimates Poisson-lognormal hurdle models

.e SJ-11-1 @net: sj 11-1 st0219!st0219@
.c sj
.a R. Raciborski
.t Right-censored Poisson regression model
.k stat-istics rcpoisson censor-ed censor-ing obs-ervations right poisson
.k reg-ressions model-s count-s data-sets set-s constant-s thresh-old
.k rcpoisson_estat rcpoisson_gof rcpoisson_p lrcpoisson post-estimations
.x
	(help @rcpoisson@, @rcpoisson_postestimation@ if installed)
	Q1/11	@browser:http://www.stata-journal.com/article.html?article=st0219!SJ11(1):95--105@
	estimates right-censored count-data models with a constant
	and variable censoring threshold

.e SJ-11-1 @net: sj 11-1 dm0053!dm0053@
.c sj
.a A. Ozimek and D. Miles
.t Geocoding and generating travel time and distance info.
.k data-sets set-s manage-ment geocod-es geocod-ing
.k traveltime-s google map-ping map-s spatial
.k info-rmation locat-ions position-s latitude-s longitude-s geograph-ically
.k system coor-dinates distance-s travel time-s arcgis
.o @geocode@, @traveltime@, if installed
.x
	Q1/11	@browser:http://www.stata-journal.com/article.html?article=dm0053!SJ11(1):106--119@
	provides latitude and longitude as well as distances
	and travel times between points utilizing Google Maps

.e SJ-11-1 @net: sj 11-1 st0220!st0220@
.c sj
.a J. M. Ramos-Goni and O. Rivero-Arias
.t Index values for the EQ-5D quality-of-life instrument
.k stat-istics eq5d index calcul-ate calcul-ations value-s quality life
.k instrum-ental euroqol
.o @eq5d@, if installed
.x
	Q1/11	@browser:http://www.stata-journal.com/article.html?article=st0220!SJ11(1):120--125@
	computes an index value using the individual mobility, self
	care, usual activities, pain or dicomfort, and anxiety or
	depression responses from the EuroQol EQ-5D quality-of-life
	instrument

.e SJ-11-1 @net: sj 11-1 dm0054!dm0054@
.c sj
.a N. J. Cox
.t Speaking Stata: Handling Roman numerals within Stata
.k data-sets set-s manage-ment
.k handl-ing roman number numerals classif-ied classif-ications
.k code-s charac-ters str-ings form regular expr-essions
.k convert toroman fromroman
.o @fromroman@, @toroman@, if installed
.x
	Q1/11	@browser:http://www.stata-journal.com/article.html?article=dm0054!SJ11(1):126--142@
	illustrates handling classification codes in string form and
	their numeric equivalents; provides commands for converting
	Roman numerals

.e SJ-11-1 st0221
.c sj
.a T. Boswell and R. G. Gutierrez
.t Tip 94: Prediction parameters for par. survival reg. models
.k tip stat-istics manip-ulation pred-ictions pred-icted param-eters
.k param-etric surviv-al reg-ressions model-s streg
.x
	Q1/11	@browser:http://www.stata-journal.com/article.html?article=st0221!SJ 11(1):143--144@				    (no commands)
	tip on manipulating prediction parameters for parametric
	survival regression models

.e SJ-11-1 st0222
.c sj
.a N. J. Horton
.t Tip 95: Estimation of error covariances in a linear model
.k tip stat-istics est-imation error-s cov-ariances xtmixed variance
.k matr-ices matr-ix mixed effect-s
.x
	Q1/11	@browser:http://www.stata-journal.com/article.html?article=st0222!SJ 11(1):145--148@				    (no commands)
	tip showing new Stata 11 features of @xtmixed@ that directly
	estimate the variance-covariance matrix

.e SJ-11-1 st0223
.c sj
.a N. J. Cox
.t Stata tip 96: Cube roots
.k tip stat-istics cube root-s graph-s graph-ing graph-ics plot-s func-tions
.x
	Q1/11	@browser:http://www.stata-journal.com/article.html?article=st0223!SJ 11(1):149--154@				    (no commands)
	tip showing the use of the cube function and cube roots

.e SJ-11-1 @net: sj 11-1 srd3_1!srd3_1@
.c sj
.t Software update for ^bound^
.a R. Goldstein
.k welsch reg-ressions bound-ed influ-ence est-imators diagnos-tics stat-istics
.o @bound@ if installed
.x
	Q1/11	@browser:http://www.stata-journal.com/article.html?article=up0031!SJ 11(1):155@
	updated to Stata 11.1

.e SJ-11-1 @net: sj 11-1 srd13_2!srd13_2@
.c sj
.a R. Goldstein
.t Software update for ^maxr2^
.k goodness fit ols ordinary least sq-uares reg-ressions
.k repli-cates covariate-s patt-erns maxr2 stat-istics
.o @maxr2@ if installed
.x
	Q1/11	@browser:http://www.stata-journal.com/article.html?article=up0031!SJ 11(1):155@
	updated to Stata 11.1; now supports factor variables and
	can be used after ^areg^ and ^ivreg2^

.e SJ-11-1 @net: sj 11-1 st0213_1!st0213_1@
.c sj
.a C. Lindsey and S. Sheather
.t Software update for ^vselect^
.k stat-istics vselect var-iables selec-tion linear reg-ressions
.k akaike-s info-rmation criterion aic bayes-ian bic stepwise forw-ard
.k selec-tion backward elim-ination mallow c nestreg-: : leap-s bound-s best
.k subset-s step_crit
.o @vselect@ if installed
.x
	Q1/11	@browser:http://www.stata-journal.com/article.html?article=up0031!SJ 11(1):155@
	^fix()^ option fixed

.e SJ-10-4 @net: sj 10-4 st0207!st0207@
.c sj
.a Y. V. Marchenko and M. G. Genton
.t Suite of commands for fitting skew-normal and skew-t models
.k stat-istics skewnreg skewtreg mskewnreg mskewtreg skewrplot fit-ting
.k skew-ness skew-ed norm-al t model-s heavy tail-s continu-ous data-sets set-s
.k multiv-ariate distrib-utions reg-ressions flex-ible param-etric univar-iate
.k plot-s resid-uals diagnos-tics nonnorm-al pred-ictions pred-icted
.k heavy tail-s mskewn_p mskewt_p skew_mahalanobis skewt_p skewn_p
.k est-imation est-imators estimat-ing
.x
	(help @skewnreg@, @skewtreg@, @mskewnreg@, @mskewtreg@,
	@skew_postestimation@, @skewrplot@ if installed)
	Q4/10	@browser:http://www.stata-journal.com/article.html?article=st0207!SJ 10(4):507--539@
	provides univariate and multivariate skew-normal and skew-t
	regressions

.e SJ-10-4 @net: sj 10-4 st0208!st0208@
.c sj
.a R. Williams
.t Fitting heterogeneous choice models with ^oglm^
.k stat-istics oglm est-imation est-imators estimat-ing model-s heterog-eneity
.k choice ordinal reg-ressions error-s variance-s param-eters linear
.k general-ized gologit-2 logit bina-ry logis-tic response-s propor-tional
.k propor-tions constrain-ts probit locat-ions scale-s oglm_ll oglm_p
.o @oglm@ if installed
.x
	Q4/10	@browser:http://www.stata-journal.com/article.html?article=st0208!SJ 10(4):540--567@
	shows how ^oglm^ (ordinal generalized linear models) can be
	used to estimate heterogeneous choice and related models

.e SJ-10-4 @net: sj 10-4 st0209!st0209@
.c sj
.a R. B. Newson
.t Frequentist q-values for multiple-test procedures
.k stat-istics qqvalue q value-s mult-iple test-s procedure-s p-values input
.k vec-tors smileplot multproc p.adjust family-wise wise err-ors rate-s
.k false discovery bonferroni sidak holm holland copenhaver hochberg simes
.k benjamini yekutieli
.o @qqvalue@ if installed
.x
	Q4/10	@browser:http://www.stata-journal.com/article.html?article=st0209!SJ 10(4):568--584@
	provides multiple-test procedures that produce q-values
	that are equal to the minimum familywise error rate or
	false discovery rate

.e SJ-10-4 @net: sj 10-4 st0210!st0210@
.c sj
.a E. Neumayer and T. Plumper
.t Making spatial analysis operational
.k stat-istics spatial anal-ysis effect-s var-iables dyad monadic spspc
.k spundir spmon spdir spagg data-sets set-s depend-ence lag-s contagion
.k target aggregate specific direct est-imation target source
.x
	(help @spspc@, @spundir@, @spmon@, @spdir@, @spagg@ if installed)
	Q4/10	@browser:http://www.stata-journal.com/article.html?article=st0210!SJ 10(4):585--605@
	facilitates spatial analysis by generating all types of
	spatial-effect variables in monadic and dyadic data, and
	in the case of dyadic data, doing so without the need for
	constructing a large 4-adic dataset

.e SJ-10-4 @net: sj 10-4 st0211!st0211@
.c sj
.a M. J. Rutherford, P. C. Lambert, and J. R. Thompson
.t Age-period-cohort modeling
.k stat-istics poprisktime apcfit age period-s cohort model-s incid-ence rate-s
.k restric-ted restric-tions cub-ic spline-s pred-icted pop-ulations time
.k lexis diagr-ams risk-s data-sets set-s mortality var-iables func-tions
.k effect-s general-ized linear carstensen sverdrup
.x
	(help @apcfit@, @poprisktime@ if installed)
	Q4/10	@browser:http://www.stata-journal.com/article.html?article=st0211!SJ 10(4):606--627@
	^apcfit^ fits age-period-cohort models overcoming the
	identifiability problem by forcing constraints on either
	the period or cohort effects; ^poprisktime^ calculates the
	population risk-time from population data

.e SJ-10-4 st0212
.c sj
.a P. Guimaraes and P. Portugal
.t Procedure to fit models with high-dimensional fixed effects
.k stat-istics fit-s model-s fix-ed effect-s high-dimensional est-imation
.k est-imators estimat-ing linear reg-ressions panel-s data-sets set-s
.k min-imums memory require-ments areg felsdvreg xtpoisson poisson speed
.x
	Q4/10	@browser:http://www.stata-journal.com/article.html?article=st0212!SJ 10(4):628--649@				    (no commands)
	describes an iterative approach for the estimation of
	linear regression models with high-dimensional fixed
	effects

.e SJ-10-4 @net: sj 10-4 st0213!st0213@
.c sj
.a C. Lindsey and S. Sheather
.t Variable selection in linear regression
.k stat-istics vselect var-iables selec-tion linear reg-ressions
.k akaike-s info-rmation criterion aic bayes-ian bic stepwise forw-ard
.k selec-tion backward elim-ination mallow c nestreg-: : leap-s bound-s best
.k subset-s step_crit
.o @vselect@ if installed
.x
	Q4/10	@browser:http://www.stata-journal.com/article.html?article=st0213!SJ 10(4):650--669@
	performs variable selection after a linear regression

.e SJ-10-4 @net: sj 10-4 gr0046!gr0046@
.c sj
.a N. J. Cox
.t Speaking Stata: Graphing subsets
.k graph-s graph-ing graph-ics plot-s subset-s group-s compar-isons
.k subdivision superimposition juxtaposition quantile-s gumbel distrib-utions
.k scat-terplots by over
.x
	Q4/10	@browser:http://www.stata-journal.com/article.html?article=gr0046!SJ 10(4):670--681@				    (no commands)
	explores graphical comparison of results for two or more
	subsets where each subset is plotted in a separate panel,
	with the rest of the data as a backdrop

.e SJ-10-4 dm0052
.c sj
.a N. J. Cox
.t Stata tip 68: Week assumptions
.k tip data-sets set-s manage-ment date-s day time week-ly assump-tions
.k func-tions mdy wofd dow mod month-ly
.x
	Q4/10	@browser:http://www.stata-journal.com/article.html?article=dm0052!SJ 10(4):682--685@				    (no commands)
	tip on Stata's solution for weeks and on how to set up
	your own alternatives given different definitions of the
	week

.e SJ-10-4 st0214
.c sj
.a L. Angquist
.t Stata tip 92: Implementation of permutations and bootstraps
.k tip stat-istics permute permu-tation boot-strapped
.x
	Q4/10	@browser:http://www.stata-journal.com/article.html?article=st0214!SJ 10(4):686--688@				    (no commands)
	tip on manually implementing permutations and bootstraps
	(instead of using @permute@ and @bootstrap@) in order to keep
	more detailed control over the data manipulations

.e SJ-10-4 gr0047
.c sj
.a V. Wiggins
.t Stata tip 93: Handling multiple y axes on ^twoway^ graphs
.k tip mult-iple axis axes y two-way way graph-s graph-ics yscale
.x
	Q4/10	@browser:http://www.stata-journal.com/article.html?article=gr0047!SJ 10(4):689--690@				    (no commands)
	tip on handling multiple y axes with @twoway@ graphs

.e SJ-10-4 @net: sj 10-4 dm0038_1!dm0038_1@
.c sj
.a R. Raciborski
.t Software update for ^kountry^
.k data-sets set-s manage-ment kountry kountryadd kountrybackup kountryrestore
.k util-ity merge comb-ine cross mult-iple source translate convert
.k convers-ions code-s scheme-s recode stand-ard stand-ardization
.k stand-ardized stand-ardisation stand-ardised form-s gen-erate
.k geograph-ically region-s var-iables name-s country
.k kountryregion-s k_capc k_cowc k_cown k_geo_cow k_geo_marc k_geo_meb
.k k_geo_men k_geo_sov k_geo_un-det k_imfn k_iso2c k_iso3c k_iso3n k_marc
.k k_mcc k_other k_stuck k_unc
.x
	(@kountry@, @kountryadd@, @kountrybackup@, @kountrynames@,
	@kountryregions@ if installed)
	Q4/10	@browser:http://www.stata-journal.com/article.html?article=up0030!SJ 10(4):691@
	update to fix ^kountry^, ^kountryadd^, ^kountrybackup^, and
	^kountryrestore^ from failing when the path to the ^PLUS^
	directory contained spaces

.e SJ-10-4 @net: sj 10-4 dm0048_1!dm0048_1@
.c sj
.a N. J. Cox
.t Software update for ^findname^
.k data-sets set-s manage-ment ds findname find name-s var-iables label-s
.k value-s patt-erns charac-teristics format-s format-ting describ-e type-s
.k look-for for search
.o @findname@ if installed
.x
	Q4/10	@browser:http://www.stata-journal.com/article.html?article=up0030!SJ 10(4):691@
	update for ^not^ option

.e SJ-10-4 @net: sj 10-4 gr42_5!gr42_5@
.c sj
.a N. J. Cox
.t Software update for ^qplot^
.k graph-s graph-ing graph-ics plot-s quantile-s quantil2 qplot
.k _gmypp
.o @qplot@ if installed
.x
	Q4/10	@browser:http://www.stata-journal.com/article.html?article=up0030!SJ 10(4):691@
	better handling of axis titling and missing values

.e SJ-10-4 @net: sj 10-4 pr0041_1!pr0041_1@
.c sj
.a N. J. Cox
.t Software update for ^corrci^
.k stat-istics prog-ramming prog-rams corr-elations conf-idence fisher-s z
.k transfo-rmations inv-erse hyperbol-ic tan-gent tanh func-tions corrci-i
.k interv-als matr-ix matr-ices multiv-ariate anal-ysis mata
.k boot-strapped pearson-s bivar-iate norm-al atan-h sinh cosh sin-e cos-ine
.k trig-onometric exp-onential odd-s arc tan-gent arctan-gent bias correct-ion
.k correct-ed prob-abilities prob-ability plot-s plot-ting sample-s samp-ling
.k distrib-utions efron num-bers num-eric var-iables miss-ing value-s
.k immed-iate
.o @corrci@, @corrcii@ if installed
.x
	Q4/10	@browser:http://www.stata-journal.com/article.html?article=up0030!SJ 10(4):691@
	update to fix ^corrci^ so that it always saves r-class results

.e SJ-10-4 @net: sj 10-4 st0015_6!st0015_6@
.c sj
.a T. J. Steichen and N. J. Cox
.t Software update for ^concord^
.k stat-istics concord-ance corr-elations coef-ficients lin graph-s graph-ics
.k limit-s agree-ment meas-urements compar-isons
.o @concord@ if installed
.x
	Q4/10	@browser:http://www.stata-journal.com/article.html?article=up0030!SJ 10(4):691@
	update explicitly supporting ^plot()^ and ^addplot()^ and
	allowing systematic control of the reference line

.e SJ-10-4 @net:sj 10-4 st0035_1!st0035_1@
.c sj
.a R. Newson & The ALSPAC Study Team
.t Software update for ^smileplot^
.k stat-istics graph-ics graph-ing graph-s plot-s smile mult-iple compar-isons
.k test-s test-ing closed data-mining mining err-ors rate-s family-wise wise
.k false discovery bonfer-ronis holm-s sidak-s holland-s copenhaver-s liu-s
.k hochberg-s rom-s simes benjamini-s yekutieli-s krieger-s p-values value-s
.k fwer fdr parapet line-s smileplot-7 multproc
.o @smileplot@ if installed
.x
	Q4/10	@browser:http://www.stata-journal.com/article.html?article=up0030!SJ 10(4):691@
	updated to Stata 10 and ^addplot()^ option added

.e SJ-10-4 @net:sj 10-4 st0043_2!st0043_2@
.c sj
.a R. Newson
.t Updates for ^sencode^, ^listtex^, ^ingap^, ^factext^, & ^descsave^
.k stat-istics conf-idence interv-als ci-i p-values value-s
.k tabl-es plot-s tex latex format-s format-ting tab-ulate tab-ulations html
.k descsave dsconcat eclplot factext factmerg factref ingap
.k format-ted display-ing output-ting output-ing
.k est-imation est-imates result-s reshape
.k lincomest lincomest_p tostring listtex parmby parmest sencode
.x
	(help @descsave@, @dsconcat@, @eclplot@, @factext@, @factmerg@, @factref@,
	@ingap@, @lincomest@, @listtex@, @parmest@, @sencode@ if installed)
	Q4/10	@browser:http://www.stata-journal.com/article.html?article=up0030!SJ 10(4):692@
	updated to Stata 11 to take advantage of new capabilities
	for factor variables and multiple imputation and providing
	new options

.e SJ-10-4 @net: sj 10-4 st0145_1!st0145_1@
.c sj
.a M. Yasar, R. Raciborski, and B. Poi
.t Software update for ^opreg^
.k stat-istics opreg production func-tions est-imates est-imation selec-tion
.k bias-es bias-ed simult-aneous param-etric semi-nonparametric param-eters
.k ordinary least sq-uares ols markov output-ting output-ing input-s
.k prob-abilities prob-ability panel-s var-iables time coef-ficients meas-ures
.k olley pakes levpet opreg_p
.o @opreg@ if installed
.x
	Q4/10	@browser:http://www.stata-journal.com/article.html?article=up0030!SJ 10(4):692@
	updated to support more than two state variables, use
	third-degree polynomial expansion, and support ^predict^

.e SJ-10-4 @net: sj 10-4 st0150_3!st0150_3@
.c sj
.a M. Bia and A. Mattei
.t Software update for ^doseresponse^ and ^gpscore^
.k stat-istics est-imation est-imates dose-s response-s func-tions adjust-ed
.k general-ized propensity scor-es continu-ous treat-ments gpscore
.k doseresponse model-s est-imators bina-ry anal-ysis confound-ing caus-al
.k effect-s outcome-s weak infer-ence cond-itional distrib-utions cov-ariances
.k covariate-s var-iables bal-anced effect-s reg-ressions boot-strapped
.k bias-ed output-ting output-ing doseresponse_model gpscore_model
.o @doseresponse@, @gpscore@ if installed
.x
	Q4/10	@browser:http://www.stata-journal.com/article.html?article=up0030!SJ 10(4):692@
	updated to Stata 11

.e SJ-10-4 @net: sj 10-4 st0182_1!st0182_1@
.c sj
.a M. L. Buis
.t Software update for ^ldecomp^
.k stat-istics indirect direct effect-s logit model-s total-s norm-ally
.k distrib-utions distrib-uted boot-strapped boot-strapping ldecomp _ldecomp
.k control-s var-iables stand-ard error-s est-imates cat-egorical effect-s
.k estimat-ing logis-tic reg-ressions conf-idence interv-als
.o @ldecomp@ if installed
.x
	Q4/10	@browser:http://www.stata-journal.com/article.html?article=up0030!SJ 10(4):692@
	bug fix for ^ldecomp^

.e SJ-10-3 @net: sj 10-3 st0196!st0196@
.c sj
.a M. Wittenberg
.t Intro. to maximum entropy and minimum cross-entropy est.
.k stat-istics maxentropy max-imum entro-py min-imums cross est-imation
.k est-imates prob-ability prob-abilities distrib-utions
.k inv-erse extreme total-s calibra-tion survey-s multiplica-tive
.k meth-ods survwgt jaynes calmar maxentlambda_d2
.o @maxentropy@ if installed
.x
	Q3/10	@browser:http://www.stata-journal.com/article.html?article=st0196!SJ 10(3):315--330@
	estimates a probability distribution using a maximum entropy
	or minimum cross-entropy criterion

.e SJ-10-3 @net: sj 10-3 st0197!st0197@
.c sj
.a S. Weber
.t ^bacon^: detect outliers in multivariate data
.k stat-istics bacon outlier-s multiv-ariate detect-able data-sets set-s mata
.k hadimvo block-ed adaptive efficient nominator-s
.o @bacon@ if installed
.x
	Q3/10	@browser:http://www.stata-journal.com/article.html?article=st0197!SJ 10(3):331--338@
	identifies potential outliers in multivariate data, even on
	large datasets of tens of thousands of observations

.e SJ-10-3 st0198
.c sj
.a R. B. Newson
.t Pred. powers of survival mod. using Harrell's C or Somers' D
.k stat-istics somer-sd estat concord-ance harrell-s c d stcox streg
.k pred-ictions pred-icted surviv-al model-s valid-ation valid-ate rank-s
.k meth-ods param-eters power-s conf-idence interv-als compar-isons compar-e
.k kendall-s tau limit-s
.x
	Q3/10	@browser:http://www.stata-journal.com/article.html?article=st0198!SJ 10(3):339--358@				    (no commands)
	illustrates producing statistically sensible confidence
	intervals and p-values for the differences between the
	predictive powers of different survival models using
	Harrell's C or Somers' D

.e SJ-10-3 @net: sj 10-3 st0199!st0199@
.c sj
.a J. C. Huber Jr.
.t Using Stata with PHASE and Haploview
.k stat-istics phase phasein phaseout haploviewout haploview haplotype-s
.k haplologit genotype-s gene-tics expor-ting import-ing
.k format-s format-ting format-ted data-sets set-s
.x
	(help @phasein@, @phaseout@, @haploviewout@ if installed)
	Q3/10	@browser:http://www.stata-journal.com/article.html?article=st0199!SJ 10(3):359--368@
	exports genotype data stored in Stata to PHASE; imports the
	inferred haplotypes back into Stata; exports haplotype/single
	nucleotide polymorphism data from Stata to Haploview

.e SJ-10-3 @net: sj 10-3 st0200!st0200@
.c sj
.a I. R. White
.t ^simsum^: Analyses of simul. studies incl. Monte Carlo error
.k stat-istics simsum data-sets set-s anal-yses simul-ations studies study
.k monte carlo error-s report-ing bias-es bias-ed empir-ical stand-ard
.k relativ-e precis-ion ave-rages model-s model-ing based sandw-ich variance-s
.o @simsum@ if installed
.x
	Q3/10	@browser:http://www.stata-journal.com/article.html?article=st0200!SJ 10(3):369--385@
	analyzes data from simulation studies and can report bias,
	coverage, power, empirical standard error, relative precision,
	aversage model-based standard error, and the relative error of
	the standard error; Monte Carlo errors are available for all
	of these quantities

.e SJ-10-3 @net:sj 10-3 st0013_2!st0013_2@
.c sj
.a P. Royston and F. M.-S. Barthel
.t Projection of power and events in clinical trials
.k stat-istics samp-les size determ-ination test-s test-ing
.k log-ranks rank-s box-es menu-s dial-ogs dial-ogues time vary-ing haz-ards
.k cross-over tarone ware harrington fleming trend surviv-al bina-ry outcome-s
.k fail-ure rct-s rand-omized control-led trial-s ernull errange
.k art one-sided alpha artbin artbindlg artformatnos artmenu artpep artpepdlg
.k artsurv artsurvdlg
.x
	(help @artbin@, @artbindlg@, @artmenu@, @artpep@, @artpepdlg@,
	@artsurv@, @artsurvdlg@, @artwhastsnew@ if installed)
	Q3/10	@browser:http://www.stata-journal.com/article.html?article=st0013_2!SJ 10(3):386--394@
	ARTPEP projects the power and events of a clinical trial
	with a time-to-event outcome into the future

.e SJ-10-3 @net:sj 10-3 st0201!st0201@
.c sj
.a E. Kontopantelis and D. Reeves
.t ^metaan^: Random-effects meta-analysis
.k stat-istics metaan meta anal-ysis max-imum like-lihood profile restric-ted
.k permu-tation model-s rand-om effect-s heterog-eneity between study studies
.k variance-s est-imates forest plot-s graph-ing metaeff two 2 stage
.k conf-idence interv-als dersimonian laird reml
.o @metaan@ if installed
.x
	Q3/10	@browser:http://www.stata-journal.com/article.html?article=st0201!SJ 10(3):395--407@
	performs fixed- or random-effects meta-analysis with choice
	of DerSimonian and Laird approach or maximum likelihood,
	profile likelihood, restricted maximum likelihood, or a
	permutation model

.e SJ-10-3 @net:sj 10-3 st0202!st0202@
.c sj
.a E. T. Parner and P. K. Andersen
.t Regression analysis of censored data using pseudo-obs.
.k stat-istics stpsurv stpci stpmean pseudo value-s surviv-al func-tions
.k cumul-ative distrib-utions prob-ability prob-abilities
.k reg-ressions model-s anal-ysis censor-ed censor-ing mean-s time incid-ence
.k event right obs-ervations restric-ted restric-tions
.x
	(help @stpsurv@, @stpci@, @stpmean@ if installed)
	Q3/10	@browser:http://www.stata-journal.com/article.html?article=st0202!SJ 10(3):408--422@
	produces pseudo-observations for use in direct regression
	modeling of the survival function, the restricted mean, and
	the cumulative incidence function in competing risks with
	right-censored data

.e SJ-10-3 @net:sj 10-3 st0203!st0203@
.c sj
.a M. Frolich and B. Melly
.t Estimation of quantile treatment effects with Stata
.k stat-istics ivqte locreg est-imates est-imation est-imators quantile-s
.k treat-ments cond-itional unconditional exog-enous exog-eneity effect-s
.k nonpar-ametric non param-etric reg-ressions var-iables instrum-ental
.k class-ical analytical std err-ors stand-ard local linear logit moremata
.k kdens smooth-ing param-eters
.o @ivqte@ and @locreg@ if installed
.x
	Q3/10	@browser:http://www.stata-journal.com/article.html?article=st0203!SJ 10(3):423--457@
	provides: Koenker and Bassett classical quantile regression
	estimator extended to heteroskedasticity consistent standard
	errors; Abadie, Angrist, and Imbens instrumental-variable
	quantile regression estimator; Firpo unconditional quantile
	treatment effects estimator; and Frolich and Melly instrumental-
	variable estimator for unconditional quantile treatment effects

.e SJ-10-3 @net:sj 10-3 dm0050!dm0050@
.c sj
.a F. Belotti and D. Depalo
.t Translation from narrative text to standard codes variables
.k data-sets set-s manage-ment screening keyword-s text-s var-iables user-s
.k def-ine abbrev-iations abbrev-iate typo-s str-ings extrac-tion reorganize
.k match-ing code-s stand-ard scheme-s mata
.o @screening@ if installed
.x
	Q3/10	@browser:http://www.stata-journal.com/article.html?article=dm0050!SJ 10(3):458--481@
	examines the content of complex narrative-text variables
	to identify one or more user-defined keywords

.e SJ-10-3 st0204
.c sj
.a N. J. Cox
.t Speaking Stata: The limits of sample skewness and kurtosis
.k stat-istics skew-ness kurt-osis func-tions samp-les samp-ling size
.k mata descrip-tive distrib-utions shape mom-ents log-normal norm-al skew-ed
.k base percent-ages
.x
	Q3/10	@browser:http://www.stata-journal.com/article.html?article=st0204!SJ 10(3):482--495@				    (no commands)
	uses Stata and Mata to show that sample skewness and
	kurtosis are limited by sample size and that these limits
	impart bias to estimation

.e SJ-10-3 st0205
.c sj
.a P. A. Lachenbruch
.t Tip 89: Means and percentiles following multiple imputation
.k tip stat-istics est-imates est-imation est-imating mean-s percent-iles
.k mult-iple imput-e imput-ing imput-ation summ-arize centile-s
.x
	Q3/10	@browser:http://www.stata-journal.com/article.html?article=st0205!SJ 10(3):496--499@				    (no commands)
	tip demonstrates using @mi@ to obtain multiply-imputed basic
	descriptive statistics

.e SJ-10-3 st0206
.c sj
.a M. Weiss
.t Stata tip 90: Displaying partial results
.k tip stat-istics display-ing partial result-s keep est-imates tabl-es drop
.x
	Q3/10	@browser:http://www.stata-journal.com/article.html?article=st0206!SJ 10(3):500--502@				    (no commands)
	tip on using @estimates table@ to display partial results

.e SJ-10-3 dm0051
.c sj
.a N. J. Cox
.t Tip 91: Putting unabbreviated varlists into local macros
.k tip data-sets set-s manage-ment varlist-s local-ly macro-s unabbreviated
.k unab expand
.x
	Q3/10	@browser:http://www.stata-journal.com/article.html?article=dm0051!SJ 10(3):503--504@				    (no commands)
	tip on interactively using @unab@ to expand a varlist and
	place the resulting unabbreviated varlist in a local macro

.e SJ-10-3 @net: sj 10-3 st0140_2!st0140_2@
.c sj
.a K. C. Longest and S. Vaisey
.t ^fuzzy^: prog. for performing qualitative comp. analyses (QCA)
.k stat-istics fuzzy prog-ramming prog-rams qualita-tive compar-isons compar-e
.k anal-ysis cmvom cnfgen coincid coverage fzplot
.k mavmb reduce setgen suffnec truthtab yavyb yvn yvo yvv yvy set-s
.k multiv-ariate data-sets boolean logit logic-al dicho-tomous
.k out-comes comb-inations cat-egorical
.k var-iables post-estimations est-imation est-imates command-s
.x
	(help @fuzzy@, @cmvom@, @cnfgen@, @coincid@, @coverage@, @fzplot@,
	@mavmb@, @reduce@, @setgen@, @suffnec@, @truthtab@, @yavyb@, @yvn@,
	@yvo@, @yvv@, @yvy@ if installed)
	Q3/10	@browser:http://www.stata-journal.com/article.html?article=up0029!SJ 10(3):505@
	a bug in ^setgen^ with the ^drect^ extension has been fixed

.e SJ-10-2 @net: sj 10-2 st0187!st0187@
.c sj
.a S. Kolenikov
.t Resampling variance estimation for complex survey data
.k stat-istics bs4rw bsweights resamp-ling samp-ling variance-s est-imation
.k complex survey-s data-sets set-s bal-anced repeat-ed replic-ations
.k repli-cates jack-knifed jack-nifed boot-strapped boot-strapping svy
.k est-imators estimat-ing replacem-ent mean-s weight-ing weight-s
.k domain design-s based doubly robust post-stratification error-s sq-uared
.o @bsweights@ if installed
.x
	Q2/10	@browser:http://www.stata-journal.com/article.html?article=st0187!SJ 10(2):165--199@
	discusses the main approaches to resampling variance
	estimation in complex survey data: balanced repeated
	replication, the jackknife, and the bootstrap

.e SJ-10-2 @net: sj 10-2 st0188!st0188@
.c sj
.a C. Lindsey and S. Sheather
.t Optimal power transformation via inverse response plots
.k stat-istics irp inv-erse response-s plot-s graph-s graph-ing graph-ics
.k optimal power transfo-rmations pred-ictors scat-terplots fit-ted fit-s
.k scale-d reg-ressions resid-uals sum square-s
.o @irp@ if installed
.x
	Q2/10	@browser:http://www.stata-journal.com/article.html?article=st0188!SJ 10(2):200--214@
	provides the inverse response plot of a response on its
	predictors

.e SJ-10-2 @net: sj 10-2 st0189!st0189@
.c sj
.a C. Lindsey and S. Sheather
.t Model fit assessment via marginal model plots
.k stat-istics mmp marginal model-s plot-s fit-ted fit-s reg-ressions
.k nonpar-ametric non param-etric semi-nonparametric lowess smooth-ing lpoly
.k glm logis-tic linear graph-s graph-ing graph-ics
.o @mmp@ if installed
.x
	Q2/10	@browser:http://www.stata-journal.com/article.html?article=st0189!SJ 10(2):215--225@
	provides marginal model plots for a regression model

.e SJ-10-2 @net: sj 10-2 st0190!st0190@
.c sj
.a N. Pantazis and G. Touloumi
.t Longitudinal data in the presence of informative drop-out
.k stat-istics jmre1 jmre1_p datajoint1 miss-ing longi-tudinal data-sets set-s
.k drop out joint multiv-ariate rand-om effect-s restric-ted restric-tions
.k iter-ative general-ized least sq-uares em algor-ithms mata est-imates
.k est-imation xtmixed manip-ulation predict fit-ted fit-s value-s bayes-ian
.k l_jmre1
.x
	(help @jmre1@, @jmre1_p@, @datajoint1@ if installed)
	Q2/10	@browser:http://www.stata-journal.com/article.html?article=st0190!SJ 10(2):226--251@
	implements a joint multivariate random effects model to
	adjust for informative drop-out in longitudinal data
	analysis

.e SJ-10-2 st0191
.c sj
.a J. Muro, C. Suarez, and M. Zamora
.t Murphy-Topel corrected variances in heckprobit with endog.
.k stat-istics murphy topel variance-s heckprob heckprobit probit
.k endog-enous endogeneity correct-ed
.k matr-ix max-imum like-lihood bina-ry choice model-s
.k var-iables two-step step est-imation est-imates qualita-tive
.x
	Q2/10	@browser:http://www.stata-journal.com/article.html?article=st0191!SJ 10(2):252--258@				    (no commands)
	shows how to obtain Murphy-Topel corrected variances for a
	two-step estimation of a heckprobit model with endogeneity
	in the main equation

.e SJ-10-2 st0192
.c sj
.a V. Verardi and C. Dehon
.t Multivariate outlier detection in Stata
.k stat-istics multiv-ariate outlier-s detect-able robust mcd est-imates
.k est-imation est-imators anal-ysis fast min-imums cov-ariances det-erminants
.k locat-ions param-eters scale-s matr-ix matr-ices
.x
	(type ^findit mcd^ to obtain the ^mcd^ command)		     (no commands)
	Q2/10	@browser:http://www.stata-journal.com/article.html?article=st0192!SJ 10(2):259--266@
	presents the minimum covariance determinant estimator

.e SJ-10-2 @net: sj 10-2 st0193!st0193@
.c sj
.a Y. Ji and C. Lee
.t Data envelopment analysis
.k stat-istics dea data-sets set-s envelopment anal-ysis linear prog-ramming
.k prog-rams efficiency optimi-zation nonpar-ametric non param-etric
.o @dea@ if installed
.x
	Q2/10	@browser:http://www.stata-journal.com/article.html?article=st0193!SJ 10(2):267--280@
	provides a linear programming method for assessing
	efficiency and productivity of decision-making units

.e SJ-10-2 @net: sj 10-2 dm0048!dm0048@
.c sj
.a N. J. Cox
.t Speaking Stata: Finding variables
.k data-sets set-s manage-ment ds findname find name-s var-iables label-s
.k value-s patt-erns charac-teristics format-s format-ting describ-e type-s
.k look-for for search
.o @findname@ if installed
.x
	Q2/10	@browser:http://www.stata-journal.com/article.html?article=dm0048!SJ 10(2):281--296@
	produces a list of variable names showing which variables
	have specific properties, such as being of string type, or
	having value labels attached, or having a date format

.e SJ-10-2 gn0050
.c sj
.a W. D. Dupont
.t Review of ^Multivariable Model-Building^
.k book-s text-s review stat-istics multiv-ariate model-s building royston
.k sauerbrei reg-ressions anal-ysis frac-tional poly-nomials model-ing
.k continu-ous var-iables
.x
	Q2/10	@browser:http://www.stata-journal.com/article.html?article=gn0050!SJ 10(2):297--302@				    (no commands)
	book review of ^Multivariable Model-Building: A Pragmatic^
	^Approach to Regression Analysis Based on Fractional^
	^Polynomials for Modeling Continuous Variables^, by
	P. Royston and W. Sauerbrei

.e SJ-10-2 dm0049
.c sj
.a B. Rising
.t Stata tip 86: The @missing()@ function
.k data-sets set-s manage-ment miss-ing func-tions prog-ramming prog-rams
.k value-s tip
.x
	Q2/10	@browser:http://www.stata-journal.com/article.html?article=dm0049!SJ 10(2):303--304@				    (no commands)
	tip on using the ^missing()^ function to deal with missing
	values

.e SJ-10-2 st0194
.c sj
.a M. L. Buis
.t Tip 87: Interpretation of interactions in nonlinear models
.k stat-istics nonlin-ear interact-ions model-s logit poisson inteff inteff3
.k marginal effect-s margin-s tip
.x
	Q2/10	@browser:http://www.stata-journal.com/article.html?article=st0194!SJ 10(2):305--308@				    (no commands)
	tip on interpreting interactions in nonlinear models
	such as @logit@ or @poisson@

.e SJ-10-2 st0195
.c sj
.a C. F. Baum
.t Tip 88: Efficiently evaluating elasticities with @margins@
.k stat-istics margin-s marginal effect-s elas-ticities semielas-ticities
.k post-estimations est-imation est-imates tip
.x
	Q2/10	@browser:http://www.stata-journal.com/article.html?article=st0195!SJ 10(2):309--312@				    (no commands)
	tip on evaluating elasticities and semielasticities with
	the @margins@ command

.e SJ-10-2 @net: sj 10-2 st0173_1!st0173_1@
.c sj
.a V. Verardi and C. Croux
.t Software update for ^mcd^
.k stat-istics robust reg-ressions anal-ysis outlier-s data-sets set-s rreg
.k qreg est-imates est-imation est-imators mcd mmregress mregress msregress
.k sregress ols ordinary least sq-uares linear vert-ically gauss-ian lever-age
.k point-s variance-s resid-uals graph-s graph-ing graph-ics
.k med-ians simul-ations
.x
	(@mmregress@, @sregress@, @msregress@, @mregress@, @mcd@ if installed)
	Q2/10	@browser:http://www.stata-journal.com/article.html?article=up0028!SJ 10(2):313@
	^outlier^ option replaced by ^generate()^ option in ^mcd^

.e SJ-10-2 @net: sj 10-2 st0099_1!st0099_1@
.c sj
.a K. J. Archer, S. Lemeshow, and M. I. Lichter
.t Software update for ^svylogitgof^
.k svylogitgof goodness of fit survey-s svy-: : design-s logis-tic logit
.k reg-ressions est-imation est-imates test-s test-ing pearson-s chi-squared
.k sq-uared chi-2 2 samp-ling samp-les size-s pseudo max-imum like-lihood
.k func-tions est-imators stat-istics
.x
	(help @svylogitgof@ if installed)
	Q2/10	@browser:http://www.stata-journal.com/article.html?article=up0028!SJ 10(2):313@
	^svylogitgof^ has been improved

.e SJ-10-1 gn0048
.c sj
.a N. J. Cox
.t A conversation with Kit Baum
.k baum interview histor-y anniversary stata journal-s econ-ometrics repec ssc
.x
	Q1/10	@browser:http://www.stata-journal.com/article.html?article=gn0048!SJ 10(1):3--8@				    (no commands)
	interview with Kit Baum

.e SJ-10-1 gn0049
.c sj
.a T. Timberlake and N. J. Cox
.t Ana Isabel Palma Carlos Timberlake (1943-2009)
.k ana timberlake obituary
.x
	Q1/10	@browser:http://www.stata-journal.com/article.html?article=gn0049!SJ 10(1):9--10@				    (no commands)
	obituary

.e SJ-10-1 @net: sj 10-1 st0182!st0182@
.c sj
.a M. L. Buis
.t Direct and indirect effects in a logit model
.k stat-istics indirect direct effect-s logit model-s total-s norm-ally
.k distrib-utions distrib-uted boot-strapped boot-strapping ldecomp _ldecomp
.k control-s var-iables stand-ard error-s est-imates cat-egorical effect-s
.k estimat-ing logis-tic reg-ressions conf-idence interv-als
.o @ldecomp@ if installed
.x
	Q1/10	@browser:http://www.stata-journal.com/article.html?article=st0182!SJ 10(1):11--29@
	decompose a total effect in a logit model into direct and
	indirect effects

.e SJ-10-1 @net: sj 10-1 dm0045!dm0045@
.c sj
.a P. W. Jeanty
.t Using the WDI database for statistical analysis in Stata
.k stat-istics data-sets set-s manage-ment wdireshape database base anal-ysis
.k world development indicators wdi economic panel-s seemingly unrel-ated
.k reg-ressions cross section-al model-ing var-iables label-s paverage
.k reshape ave-rages time-series series
.o @wdireshape@, @paverage@ if installed
.x
	Q1/10	@browser:http://www.stata-journal.com/article.html?article=dm0045!SJ 10(1):30--45@
	enables efficient management of world development indicators
	datasets

.e SJ-10-1 st0183
.c sj
.a B. Jann and J. S. Long
.t Tabulating SPost results using ^estout^ and ^esttab^
.k stat-istics tab-ulate spost result-s estadd esttab estout post-estimation
.k command-s compute reg-ressions model-s brant fitstat prvalue prchange
.k listcoef mlogtest asprvalue table-s
.x
	Q1/10	@browser:http://www.stata-journal.com/article.html?article=st0183!SJ 10(1):46--60@				    (no commands)
	facilitates tabulating results from the ^SPost^ user package
	via the ^estout^ user package

.e SJ-10-1 @net: sj 10-1 gr0044!gr0044@
.c sj
.a M. Falcaro and A. Pickles
.t ^riskplot^: aid to invest. effect of mult. cat. risk factors
.k stat-istics riskplot graph-s graph-ing graph-ics graph-ical effect-s
.k mult-iply mult-iple cat-egorical risk-s factor-s dend-rograms plot-s
.k plot-ting mean-s scor-es risk-s abs-olute clus-ters clus-tering anal-ysis
.o @riskplot@ if installed
.x
	Q1/10	@browser:http://www.stata-journal.com/article.html?article=gr0044!SJ 10(1):61--68@
	provides a graphical aid to assess the strength, importance,
	and consistency of multiple categorical risk factors

.e SJ-10-1 @net: sj 10-1 st0184!st0184@
.c sj
.a C. Lindey and S. Sheather
.t Power transformation via multivariate Box-Cox
.k stat-istics mboxcox mbctrans power transfo-rmations multiv-ariate scale-d
.k est-imation est-imators estimat-ing norm-ality
.k linear var-iables box-cox cox reg-ressions transfo-rmed process-es
.o @mboxcox@, @mbctrans@ if installed
.x
	Q1/10	@browser:http://www.stata-journal.com/article.html?article=st0184!SJ 10(1):69--81@
	computes the normalizing scaled power transformations for a
	set of variables via the multivariate Box-Cox transformation

.e SJ-10-1 @net: sj 10-1 st0185!st0185@
.c sj
.a K. Mihaly, D. F. McCaffrey, J. R. Lockwood, and T. R. Sass
.t Centering and ref. groups for fixed eff.: Mod. to ^felsdvreg^
.k stat-istics felsdvreg felsdvregdm center refer-ence group-s est-imates
.k fix-ed effect-s modifi-cation modify multi-level level longi-tudinal
.k database base panel-s data-sets set-s model-s fix-ed effect-s fit-ting
.k param-eters sum-s zero constrain-ts mean-s std err-ors stand-ard shrink
.k dimen-sional high time vary-ing infer-ence one 1 two 2 level areg xt-reg fe
.x
	(help @felsdvregdm@ if installed)
	Q1/10	@browser:http://www.stata-journal.com/article.html?article=st0185!SJ 10(1):82--103@
	provides parameterization of fixed-effects models using
	sum-to-zero constraints that provides estimates of fixed
	effects relative to mean effects within well-defined
	reference groups

.e SJ-10-1 @net: sj 10-1 st0186!st0186@
.c sj
.a J. M. Hilbe
.t Creating synthetic discrete-reponse regression models
.k stat-istics reg-ression model-s discrete response-s creat-e creat-ed
.k creat-ing synthetic bias data-sets set-s manage-ment
.k binom-ial count-s cat-egorical
.k response-s param-eters pred-ictors continu-ous bina-ry neg-ative
.k heterog-eneity level-s number cut point-s order-ed unorder-ed
.k monte carlo simul-ations log-s link-ed linear canon-ical hurdle rnbinomial
.k rpoisson rndpoi-x
.x
	Q1/10	@browser:http://www.stata-journal.com/article.html?article=st0186!SJ 10(1):104--124@
	presents code for the creation of synthetic binomial, count,
	and categorical response models

.e SJ-10-1 @net: sj 10-1 pr0050!pr0050@
.c sj
.a W. Gould
.t Mata Matters: Stata in Mata
.k mata stata putmata getmata get put data-sets set-s manage-ment
.k vector-s matr-ix matr-ices view return var-iables move mov-ing
.o @putmata@, @getmata@
.x
	Q1/10	@browser:http://www.stata-journal.com/article.html?article=pr0050!SJ 10(1):125--142@
	introduces new official Stata commands @putmata@ and @getmata@
	for putting data from Stata to Mata and getting results back
	to Stata

.e SJ-10-1 gr0045
.c sj
.a N. J. Cox
.t Speaking Stata: The ^statsby^ strategy
.k stat-istics graph-s graph-ics statsby r-class e-class command-s data-sets
.k set-s obs-ervations result-s reduce compar-isons group-s total-s subset-s
.k box-es plot-s conf-idence interv-als
.x
	Q1/10	@browser:http://www.stata-journal.com/article.html?article=gr0045!SJ 10(1):143--151@				    (no commands)
	demonstrates the use of @statsby@ to prepare a reduced
	dataset for subsequent graphing

.e SJ-10-1 dm0046
.c sj
.a D. L. Golbe
.t Stata tip 83: Merging multilingual datasets
.k data-sets set-s manage-ment merge multiling-ual merg-ing lang-uage label-s
.k labelbook tip
.x
	Q1/10	@browser:http://www.stata-journal.com/article.html?article=dm0046!SJ 10(1):152--156@				    (no commands)
	tip on how to merge multilingual datasets

.e SJ-10-1 dm0047
.c sj
.a N. J. Cox
.t Stata tip 84: Summing missing
.k data-sets set-s manage-ment miss-ing value-s sum-ming zero tip
.x
	Q1/10	@browser:http://www.stata-journal.com/article.html?article=dm0047!SJ 10(1):157--159@				    (no commands)
	tip concerning treatment of missing data when summing

.e SJ-10-1 pr0051
.c sj
.a N. J. Cox
.t Stata tip 85: Looping over nonintegers
.k prog-ramming prog-rams loop-ing loop-s over inte-gers num-bers forvalues
.k foreach while tip
.x
	Q1/10	@browser:http://www.stata-journal.com/article.html?article=pr0051!SJ 10(1):160--163@				    (no commands)
	tip on using @forvalues@ to loop over numbers

.e SJ-10-1 @net: sj 10-1 gr0009_1!gr0009_1@
.c sj
.a N. J. Cox
.t Software update for model diagnostic graph commands
.k stat-istics graph-ics graph-ing graph-s plot-s
.k diagnos-tics reg-ressions model-s response-s var-iables
.k prob-ability predict resid-uals mspline two-way abs-olute
.k value-s root-s hetero-skedasticity hetero-skedasticity square-d
.k square-s est-imates est-imation result-s drop-lines mean-s
.k quantile-s nor-mail gauss-ian anova
.k anovaplot indexplot modeldiag ofrtplot ovfplot qfrplot racplot
.k rdplot regplot rhetplot rvfplot2 rvlrplot rvpplot2
.k smooth-ing restric-ted cub-ic spline-s rbinplot
.x
	(help @anovaplot@, @indexplot@, @modeldiag@, @ofrtplot@, @ovfplot@,
	@qfrplot@, @racplot@, @rdplot@, @regplot@, @rhetplot@, @rvfplot2@,
	@rvlrplot@, @rvpplot2@ if installed)
	Q1/10	@browser:http://www.stata-journal.com/article.html?article=up0027!SJ 10(1):164@
	provides new command ^rbinplot^ for plotting means or medians
	of residuals by bins; provides new options for smoothing
	using restricted cubic splines; updates ^anova^ examples

.e SJ-10-1 @net: sj 10-1 gr0021_1!gr0021_1@
.c sj
.a N. J. Cox
.t Software update for ^doublesm^ and ^diagsm^
.k doublesm diagsm polarsm mylabels
.k graph-s graph-ics graph-ing plot-s plot-ting stat-istics lowess
.k data-sets set-s anal-ysis bivar-iate double smooth-ing quantile-s
.k diag-onals polar coor-dinates meas-urements meas-ures pred-ictions
.k distrib-utions two-way way running line-s mean-s abs-olute dev-iations
.k med-ians stand-ardization stand-ardized stand-ardisation stand-ardised
.k univar-iate scale skew-ness skew-ed robust root-s transfo-rmations
.k outlier-s sin-e cos-ine restric-ted cub-ic spline-s
.o @doublesm@, @diagsm@, @polarsm@ if installed
.x
	Q1/10	@browser:http://www.stata-journal.com/article.html?article=up0027!SJ 10(1):164@
	option to carry out smoothing using restricted cubic splines
	added to ^doublesm^ and ^diagsm^

.e SJ-10-1 @net: sj 10-1 gr41_4!gr41_4@
.c sj
.a N. J. Cox
.t Software update for ^distplot^
.k graph-s graph-ics graph-ing quantile-s plot-s distplot qplot
.k power-s scaling distrib-utions log-normal norm-al univar-iate
.k anal-ysis split freq-uency freq-uencies egen sum-s scat-terplots
.k tukey specie-s abundance ecolog-y whittaker broken-stick stick
.o @distplot@ if installed
.x
	Q1/10	@browser:http://www.stata-journal.com/article.html?article=up0027!SJ 10(1):164@
	new ^reverse(ge)^ option specifies plotting probabilities or
	frequencies greater than or equal to any data value

.e SJ-9-4 @net: sj 9-4 st0175!st0175@
.c sj
.a F. M.-S. Barthel, P. Royston, and M. K. B. Parmar
.t Sample size in multiarm, multistage random. controlled trials
.k stat-istics samp-les samp-ling size-s calcul-ate calcul-ations multistage
.k rand-omized control-led trial-s time event outcome-s nstagedlg nstagemenu
.k nstage treat-ments test-s test-ing mult-iple exper-iments exper-imental
.k arm-s design-s meas-ures compar-isons menu-s dial-ogs dial-ogues box-es
.k num-bers rate-s one-sided alpha omega-2 power-s alloc-ation ratio-s
.k surviv-al prob-abilities prob-ability corr-elations stage
.k evfromtin4 timetoevn4
.x
	(help @nstage@, @nstagedlg@, @nstagemenu@ if installed)
	Q4/09	@browser:http://www.stata-journal.com/article.html?article=st0175!SJ 9(4):505--523@
	presents menu- and command-driven programs for calculation
	of sample size, number of events, and trial duration in
	novel multiarm, multistage, randomized controlled trials
	with a time-to-event outcome

.e SJ-9-4 st0176
.c sj
.a M. Blackwell, S. Iacus, G. King, and G. Porro
.t cem: Coarsened exact matching in Stata
.k stat-istics exact match-ing cem est-imators est-imates est-imation effect-s
.k treat-ments control-led group-s coarsened caus-al meth-ods model-s unit
.k bal-anced meas-urements var-iables covariate-s strat-ified strat-a strat-um
.k mono-tonic bound-s unmatch-ed data algor-ithms obs-ervations explicit
.k choice user-s cat-egorical recode restric-ted restric-tions weight-s
.k miss-ing value-s mult-iply mult-iple imput-e imput-ing imput-ation block-ed
.k block-ing block-s rand-omized output-ting output-ing imbalance
.x
	Q4/09	@browser:http://www.stata-journal.com/article.html?article=st0176!SJ 9(4):524--546@				    (no commands)
	introduces coarsened exact matching, a new method for
	improving the estimation of causal effects by reducing
	imbalance in covariates between treated and control groups

.e SJ-9-4 @net: sj 9-4 st0177!st0177@
.c sj
.a P. Royston and W. Sauerbrei
.t Bootstrap assessment of the stability of multivariable models
.k stat-istics boot-strapped stable stabil-ity multivariable model-s
.k frac-tional poly-nomials mfp fracpoly fraceval mfpboot_bif mfpboot
.k pmbevalfn pmbeval pmbstabil pred-ictors anal-ysis var-iables continu-ous
.k func-tions aggregate selec-tion nonpar-ametric non param-etric repli-cates
.k replic-ations corr-elations freq-uency freq-uencies
.k meas-ures curv-es mfpboot_10 pmbextract pmbload
.x
	(help @fraceval@, @mfpboot_bif@, @mfpboot@, @pmbevalfn@,
	@pmveval@, @pmbstabil@ if installed)
	Q4/09	@browser:http://www.stata-journal.com/article.html?article=st0177!SJ 9(4):547--570@
	describes tools for stability analysis in context of the
	@mfp@ command for multivariable model building

.e SJ-9-4 @net: sj 9-4 st0178!st0178@
.c sj
.a T. CorneliBen and K. Sonderhof
.t Partial effects in @probit@/@logit@ with triple dummy interact.
.k stat-istics partial effect-s probit logit model-s dum-my dum-mies
.k var-iables interact-ions term-s nonlin-ear reg-ressions coef-ficients
.k inteff3 reg-ressors pair-wise delta method-s linear
.o @inteff3@ if installed
.x
	Q4/09	@browser:http://www.stata-journal.com/article.html?article=st0178!SJ 9(4):571--583@
	analyzes partial effects in probit and logit models with
	a triple dummy-variable interaction term

.e SJ-9-4 @net: sj 9-4 st0179!st0179@
.c sj
.a W. J. Burke
.t Cragg's tobit alternative using Stata
.k stat-istics fit-ting cragg-it tobit altern-atives two 2 corner-s solutions
.k model-s limited depend-ent var-iables probit prob-abilities prob-ability
.k reg-ressions max-imum like-lihood ml-e est-imation est-imates craggit_ll
.o @craggit@ if installed
.x
	Q4/09	@browser:http://www.stata-journal.com/article.html?article=st0179!SJ 9(4):584--592@
	introduces the command ^craggit^, which simultaneousely
	fits both tiers of Cragg's "two-tier" alternative to
	@tobit@ for corner-solution models

.e SJ-9-4 @net: sj 9-4 st0180!st0180@
.c sj
.a I. Zezula
.t A new solution to the multivariate Behrens-Fisher problem
.k stat-istics multiv-ariate fisher-s behren-s problem-s hotelmnm
.k test-s test-ing mvtest mean-s welch-s hotel-lings distrib-utions
.o @hotelmnm@ if installed
.z
.x
	Q4/09	@browser:http://www.stata-journal.com/article.html?article=st0180!SJ 9(4):593--598@
	implementation of the multivariate Behrens-Fisher problem;
	see the ^heterogeneous^ option of the @mvtest means@ command
	incorporated into Stata 11.0

.e SJ-9-4 pr0049
.c sj
.a W. Gould
.t Mata Matters: File processing
.k prog-ramming prog-rams mata matr-ix matr-ices file-s process-es read-ing
.k data-sets set-s str-ings control-led character-istics problem-s cscript
.k script-s cert-ify cert-ification synt-ax loop-ing loop-s input-s input-ting
.k input-ing out-putting compound expr-essions struct-ures code-s do-files
.k routine
.x
	Q4/09	@browser:http://www.stata-journal.com/article.html?article=pr0049!SJ 9(4):599--620@				    (no commands)
	discusses how to use Mata to read into Stata datasets
	that are formatted difficultly

.e SJ-9-4 gr0041
.c sj
.a N. J. Cox
.t Speaking Stata: Paired, parallel, or profile plots
.k graph-s graph-ing graph-ics pair-s pair-ed paral-lel profile plot-s change
.k corr-elations compar-isons 2 two-way way wide long panel-s longi-tudinal
.k var-iables pcarrow data-sets set-s coor-dinates chart-s link diagr-ams
.k scat-terplots pcspike spike-s arrow-s structure map-ping reshape stack-ed
.k separ-ate rank-s name-s area-s line-s
.x
	Q4/09	@browser:http://www.stata-journal.com/article.html?article=gr0041!SJ 9(4):621--639@				    (no commands)
	explores paired, parallel, and profile plot making for
	changes, correlations, and other comparisons between
	variables

.e SJ-9-4 st0181
.c sj
.a M. Weiss
.t Tip 80: Constructing a group var. with specified group sizes
.k tip data-sets set-s manage-ment
.k group-s var-iables size egen runiform uniform-ly rand-om
.k num-eric num-bers set-s set-tings seed irecode func-tions
.x
	Q4/09	@browser:http://www.stata-journal.com/article.html?article=st0181!SJ 9(4):640--642@				    (no commands)
	tip on how to construct a group variable with specified
	group sizes

.e SJ-9-4 gr0042
.c sj
.a M. L. Buis and M. Weiss
.t Stata tip 81: A table of graphs
.k tip graph-s graph-ing graph-ics tabl-es by opt-ions cat-egorical var-iables
.k colu-mns row-s cols fillin titl-es
.x
	Q4/09	@browser:http://www.stata-journal.com/article.html?article=gr0042!SJ 9(4):643--647@				    (no commands)
	tip on how to create a table of graphs

.e SJ-9-4 @net: sj 9-4 gr0043!gr0043@
.c sj
.a N. J. Cox
.t Stata tip 82: Grounds for grids on graphs
.k tip graph-s graph-ing graph-ics grid-s horizont-ally vert-ically line-s axis
.k axes tick-s width color-s linestyle scat-terplots plot-s
.x
	Q4/09	@browser:http://www.stata-journal.com/article.html?article=gr0043!SJ 9(4):648--651@				    (no commands)
	tip on when a grid within a graph is appropriate

.e SJ-9-4 @net:sj 9-4 sg113_2!sg113_2@
.c sj
.a N. J. Cox
.t Tabulation of ^modes^
.k stat-istics mode-s tabl-es tab-ulate tab-ulations
.o @modes@ if installed
.x
	Q4/09	@browser:http://www.stata-journal.com/article.html?article=up0026!SJ 9(4):652@
	update to allow the ^generate()^ option to record in an
	indicator variable of which observations contain values
	matching any of the modes displayed

.e SJ-9-4 @net: sj 9-4 st0150_2!st0150_2@
.c sj
.a M. Bia and A. Mattei
.t The dose-response function adj. for the gen. propensity score
.k stat-istics est-imation est-imates dose-s response-s func-tions adjust-ed
.k general-ized propensity scor-es continu-ous treat-ments gpscore
.k doseresponse model-s est-imators bina-ry anal-ysis confound-ing caus-al
.k effect-s outcome-s weak infer-ence cond-itional distrib-utions cov-ariances
.k covariate-s var-iables bal-anced effect-s reg-ressions boot-strapped
.k bias-ed output-ting output-ing doseresponse_model gpscore_model
.o @doseresponse@, @gpscore@ if installed
.x
	Q4/09	@browser:http://www.stata-journal.com/article.html?article=up0026!SJ 9(4):652@
	updated to specify ^version 10^ in order to run correctly
	under Stata 11

.e SJ-9-3 @net: sj 9-3 st0169!st0169@
.c sj
.a S. Kolenikov
.t Confirmatory factor analysis using ^confa^
.k stat-istics confirm-atory factor-s anal-ysis confa max-imum like-lihood ml-e
.k post-estimations est-imation est-imates bollen-stine stine boot-strapped
.k multiv-ariate latent var-iables model-s identify-ing unobs-erved obs-erved
.k cov-ariances covariate-s matr-ix matr-ices test-s test-ing goodness of fit
.k gof param-eters distrib-utions ratio-s resamp-ling samp-ling factor-s
.k scor-es scor-ing pred-icted opt-ions variance-s estat specifica-tion
.k start-ing value-s std err-ors stand-ard robust corr-elations scale-s
.k scale-d diff-erences bentler-s indic-es corr-elate pred-ictions miss-ing
.k meas-ures meas-urements mult-iple meth-ods constrain-ts param-eters
.k confa_estat confa_lf-m confa_p
.o @confa@, @confa_estat@, @bollenstine@ if installed
.x
	Q3/09	@browser:http://www.stata-journal.com/article.html?article=st0169!SJ 9(3):329--373@
	fits confirmatory factor analysis models by maximum
	likelihood and provides diagnostics for the fitted models

.e SJ-9-3 @net: sj 9-3 gr0038!gr0038@
.c sj
.a R. Raciborski
.t Graphical rep. of multivariate data using Chernoff faces
.k graph-s graph-ing graph-ics graph-ical multiv-ariate data-sets set-s
.k chernoff face-s point-s dimen-sional clust-ers clust-ering outlier-s
.k draw-s draw-ing comb-ine classif-ications plot-s
.o @chernoff@ if installed
.x
	Q3/09	@browser:http://www.stata-journal.com/article.html?article=gr0038!SJ 9(3):374--387@
	Stata implementation of Chernoff faces

.e SJ-9-3 st0170
.c sj
.a Y. V. Marchenko and J. P. Reiter
.t Improved DOF for mult. sig. tests from MI, small-sample data
.k stat-istics degree-s freedom df multiv-ariate signif-icant signif-icance
.k test-s test-ing mult-iple imput-e imput-ing mult-iply small
.k samp-les data-sets set-s signif-icance hyp-othesis hyp-otheses imput-ation
.k mi-m miss-ing value-s ice equal-ity size fmi info-rmation frac-tion
.k adjust-ed simul-ations mvn norm-al est-imates
.k est-imation restric-ted restric-tions
.x
	Q3/09	@browser:http://www.stata-journal.com/article.html?article=st0170!SJ 9(3):388--397@				    (no commands)
	proposes improvements to existing degrees of freedom
	used for significance testing of multivariate hypotheses
	in small samples when missing data are handled using
	multiple imputation

.e SJ-9-3 @net: sj 9-3 st0171!st0171@
.c sj
.a K. Finlay and L. M. Magnusson
.t Implementing weak-instrument robust tests for IV models
.k stat-istics weak instrum-ental robust test-s test-ing general-ized class
.k var-iables model-s rivtest est-imates est-imation estimat-ing conf-idence
.k interv-als endog-enous hyp-othesis hyp-otheses est-imators linear tobit
.k probit ivtobit ivprobit limit-s limited depend-ent ldv homosce-dasticity
.k homoske-dasticity post-estimations anderson rubin-s overident-ification
.k condivreg ivreg2 min-imums distance-s resid-uals
.k hetero-scedasticity hetero-skedasticity clus-tered depend-ence iv-regress
.k variance-s joint two-stage stage 2 least
.k sq-uares exog-enous monte carlo simul-ations
.o @rivtest@ if installed
.x
	Q3/09	@browser:http://www.stata-journal.com/article.html?article=st0171!SJ 9(3):398--421@
	presents a minimum distance approach for conducting
	hypothesis testing in the presence of potentially weak
	instruments; presents weak-instrument tests for a general
	class of linear instrumental-variables models robust to
	arbitrary heteroskedasticity or intracluster dependence

.e SJ-9-3 @net: sj 9-3 st0172!st0172@
.c sj
.a D. Depalo
.t A seasonal unit-root test with Stata
.k stat-istics season-ally seasonality unit root-s test-s test-ing freq-uency
.k freq-uencies sroot determ-ination statio-nary stationarity shoc-ks
.k patt-erns adjust-ed process-es unit-circles circle-s coint-egration
.k time-series series lag-ged lag-s dum-my dum-mies quarter-ly hegy-4
.o @sroot@ if installed
.x
	Q3/09	@browser:http://www.stata-journal.com/article.html?article=st0172!SJ 9(3):422--438@
	advocates using original data instead of seasonally
	adjusted data; implements a test for unit roots in
	quarterly data

.e SJ-9-3 @net: sj 9-3 st0173!st0173@
.c sj
.a V. Verardi and C. Croux
.t Robust regression in Stata
.k stat-istics robust reg-ressions anal-ysis outlier-s data-sets set-s rreg
.k qreg est-imates est-imation est-imators mcd mmregress mregress msregress
.k sregress ols ordinary least sq-uares linear vert-ically gauss-ian lever-age
.k point-s variance-s resid-uals graph-s graph-ing graph-ics
.k med-ians simul-ations
.x
	(@mmregress@, @sregress@, @msregress@, @mregress@, @mcd@ if installed)
	Q3/09	@browser:http://www.stata-journal.com/article.html?article=st0173!SJ 9(3):439--453@
	provides alternatives to @rreg@ and @qreg@ for robust-to-outlier
	regression; presents a graphical tool that recognizes the
	type of detected outliers

.e SJ-9-3 @net: sj 9-3 st0174!st0174@
.c sj
.a S. J. Goerg and J. Kaiser
.t Nonpar. testing of distributions--the Epps-Singleton test
.k stat-istics nonpar-ametric non param-etric test-s test-ing distrib-utions
.k epps-singleton singleton two 2 samp-les samp-ling empir-ical
.k character-istics func-tions ksmirnov kol-mogorov smir-nov escftest
.k pop-ulations prob-abilities prob-ability dens-ity
.k wilcox-on mann-whitney whitney rank-sums
.o @escftest@ if installed
.x
	Q3/09	@browser:http://www.stata-journal.com/article.html?article=st0174!SJ 9(3):454--465@
	implements the nonparametric Epss-Singleton two-sample
	omnibus test using the empirical characteristic function

.e SJ-9-3 @net: sj 9-3 st0067_4!st0067_4@
.c sj
.a P. Royston
.t Mult. imp.: update of ^ice^, with emphasis on cat. variables
.k ice micombine mijoin misplit uvis cmdchk _mvis mvis
.k stat-istics data-sets set-s manage-ment miss-ing value-s
.k mult-iple multiv-ariate imput-e imput-ing imput-ation rubin-s rule-s
.k conf-idence interv-als est-imation est-imates model-s hot-deck deck
.k test-s test-ing surviv-al anal-ysis streg stcox rand-om reg-ressions
.k switch-ing pred-ictions match-ing mice box cox skew-ness skew-ed
.k ordinal restric-ted restric-tions ologit
.k censor-ed censor-ing obs-ervations right left mim reformat perfect svy
.k survey-s var-iables time event intreg outcome-s quantile-s q-qplots
.k plot-s kaplan-meier meier log-normal norm-al distrib-utions mfp
.k param-eters cat-egorical chain-ed equation-s univar-iate neg-ative nbreg
.k reg-ressions binom-ial opt-ions multi-level level prefix cond-itional
.k out-puting sample-s restric-ted restric-tions indep-endence indep-endent
.k subset-s by ice_
.o @ice@, @uvis@ if installed
.x
	Q3/09	@browser:http://www.stata-journal.com/article.html?article=st0067_4!SJ 9(3):466--477@
	update of ^ice^ package with emphasis on categorical
	variables; clarifies relationship between ^ice^ and @mi@

.e SJ-9-3 gr0039
.c sj
.a N. J. Cox
.t Speaking Stata: Creating and varying box plots
.k graph-s graph-ing graph-ics creat-e creat-ed creat-ing vary-ing box-plots
.k plot-s hbox egen two-way way structure var-iables group-s quartile-s
.k interquart-ile range iqr whisker line-s horizont-ally quantile-s
.k distrib-utions percent-iles mean-s rcap rbar rspike scat-terplots
.x
	Q3/09	@browser:http://www.stata-journal.com/article.html?article=gr0039!SJ 9(3):478--496@				    (no commands)
	explains how to use @egen@ to calculate the statistical
	ingredients needed for box plots and variations of box
	plots; shows the use of @twoway@ to then create the plots

.e SJ-9-3 pr0047
.c sj
.a J. Herrin
.t Stata tip 77: (Re)using macros in multiple do-files
.k prog-ramming prog-rams macro-s mult-iple do-files file-s local-ly global-ly
.k tip group-s subset-s value-s include-s
.x
	Q3/09	@browser:http://www.stata-journal.com/article.html?article=pr0047!SJ 9(3):497--498@				    (no commands)
	tip on the use of @include@ when defining local or
	global macros

.e SJ-9-3 gr0040
.c sj
.a N. J. Cox
.t Stata tip 78: Highlighting subsets & downplaying substrates
.k tip graph-s graph-ics graph-ing subset-s set-s style-s color-style .gph gph
.k black gray-scale grey-scale scale-s white scheme-s shad-es shad-ing two-way
.k way hist-ograms scat-terplots plot-s mkspline spline-s smooth-ing
.x
	Q3/09	@browser:http://www.stata-journal.com/article.html?article=gr0040!SJ 9(3):499--503@				    (no commands)
	tips on how to use gray to highlight subsets and
	downplay substrates in graphs

.e SJ-9-3 pr0048
.c sj
.a N. J. Cox
.t Stata tip 79: Optional arguments to options
.k tip prog-rams prog-ramming opt-ions arg-uments simple complex synt-ax
.k pars-e pars-ing
.x
	Q3/09	@browser:http://www.stata-journal.com/article.html?article=pr0048!SJ 9(3):504@					    (no commands)
	tip showing programmers how to provide an option that
	can be specified with or without arguments

.e SJ-9-2 st0162
.c sj
.a P. Cummings
.t Methods for estimating adjusted risk ratios
.k stat-istics est-imates est-imation meth-ods adjust-ed risk-s ratio-s
.k mantel-haenszel haenszel inv-erse variance-s general-ized linear
.k reg-ressions case-control control-s odds outcome-s incid-ence irr-s
.k logis-tic cond-itional clogit adjust-ed expos-ures expos-ed pop-ulations
.k conf-idence interv-als strat-ified log-s link-ed binom-ial distrib-utions
.k converg-ence robust est-imators glm poisson std err-ors stand-ard cox
.k propor-tional haz-ards stand-ardization stand-ardized stand-ardisation
.k stand-ardised substitut-ion boot-strapped match-ed
.x
	Q2/09	@browser:http://www.stata-journal.com/article.html?article=st0162!SJ 9(2):175--196@				    (no commands)
	discusses several methods for estimating adjusted risk ratios
	and shows how they can be executed in Stata

.e SJ-9-2 @net: sj 9-2 sbe19_6!sbe19_6@
.c sj
.a R. M. Harbord, R. J. Harris, and J. A. C. Sterne
.t Updated tests for small-study effects in meta-analyses
.k stat-istics meta-bias anal-ysis bias publication begg mezumdar
.k egger test-s test-ing ktau2 ifexp funnel plot-s plot-ting asym-metry
.k sym-metry metan effect-s est-imation est-imates scat-terplots
.x
	(@metabias@ if installed)
	Q2/09	@browser:http://www.stata-journal.com/article.html?article=sbe19_6!SJ 9(2):197--210@
	describes an updated version of the ^metabias^ command
	providing statistical tests for funnel plot asymmetry

.e SJ-9-2 @net: sj 9-2 st0163!st0163@
.c sj
.a R. M. Harbord and P. Whiting
.t metandi: Meta-anal. of diag. acc. using hier. logistic reg.
.k stat-istics metan-diplot post-estimations est-imation est-imates meta
.k anal-ysis diagnos-tics accur-acy hier-archical logis-tic reg-ressions
.k test-s test-ing multi-level level model-s gllamm general-ized mixed
.k sensitiv-ity specifici-ty xt-melogit roc receiver-s operating
.k character-istics curv-es plot-s plot-ting graph-s graph-ics graph-ing
.k pred-ictions bivar-iate logit param-eters cook-sd d distance-s
.k method-s formula conf-idence region-s metandi_p
.x
	(help @metandi@, @metandiplot@, @metandi_postestimation@
	if installed)
	Q2/09	@browser:http://www.stata-journal.com/article.html?article=st0163!SJ 9(2):211--229@
	introduces the command ^metandi^ for meta-analyzing
	diagnostic accuracy data

.e SJ-9-2 @net: sj 9-2 st0164!st0164@
.c sj
.a P. Royston and W. Sauerbrei
.t Interactions between treat. & cont. covar. in clin. trials
.k stat-istics interact-ions treat-ments continu-ous covariate-s control-led
.k trial-s bina-ry multivariable frac-tional poly-nomials subpop-ulations
.k treat-ments effect-s mfp-i plot-s plot-ting stepp tail-s win-dows patt-erns
.k post-estimations est-imation est-imates algor-ithms pred-ictors group-s
.k func-tions variant var-iables param-eters cat-egorical opt-ions linear
.k model-s graph-s graph-ing graph-ics kaplan-meier meier
.k mfpi_plot stepp_plot stepp_tail stepp_window
.o @mfpi@ if installed
.x
	Q2/09	@browser:http://www.stata-journal.com/article.html?article=st0164!SJ 9(2):230--251@
	provides two techniques to detect and model interactions
	between treatment and continuous covariates in clinical
	trials

.e SJ-9-2 @net: sj 9-2 st0139_1!st0139_1@
.c sj
.a P. Royston, J. B. Carlin, and I. R. White
.t Multiple imputation of missing values: New features for ^mim^
.k stat-istics manage-ment anal-ysis mult-iply mult-iple imput-e imput-ing
.k imput-ation miss-ing value-s data-sets set-s stack-ed vert-ically mim
.k ice micombine rand-om comb-ine store est-imates est-imation param-eters
.k post-estimations manip-ulation transfo-rmations reshape append merge
.k check-s replay propor-tions logis-tic mimstack monte carlo error-s mice
.k jack-knifed jack-nifed cat-egory rubin-s statsby byvar frac-tional
.k pred-icted pred-ictions test-s test-ing fisher
.x
	(help @byvar@, @mim@, @mimstack@ if installed)
	Q2/09	@browser:http://www.stata-journal.com/article.html?article=st0139_1!SJ 9(2):252--264@
	update for ^mim^, a program for managing multiply imputed
	datasets and performing inference

.e SJ-9-2 @net: sj 9-2 st0165!st0165@
.c sj
.a P. C. Lambert and P. Royston
.t Further dev. of flexible param. models for survival analysis
.k stat-istics flex-ible param-etric model-s surviv-al anal-ysis stpm-2 time
.k depend-ent effect-s propor-tional haz-ards baseline func-tions log-s
.k cumul-ative spline-s restric-ted restric-tions cub-ic like-lihood
.k param-eters ratio-s scale-s pred-icted pred-ictions entry risk-s relativ-e
.k post-estimations est-imation est-imates stcox cox
.k reg-ressions stsplit split fit-ted fit-s st-set incid-ence rate-s mult-iple
.k stpm2_ml_hazard-_rs stpm2_ml_normal-_rs stpm2_ml_odds-_rs
.k stpm2_ml_theta-_rs stpm2_pred
.x
	(help @stpm2@, @stpm2_postestimation@ if installed)
	Q2/09	@browser:http://www.stata-journal.com/article.html?article=st0165!SJ 9(2):265--290@
	introduces ^stpm2^, which extends the class of flexible
	parametric survival models programmed with ^stpm^

.e SJ-9-2 st0166
.c sj
.a A. Dinno
.t Horn's parallel anal. for prin. comp. anal. and factor anal.
.k stat-istics parallel-ized anal-ysis princ-ipal compon-ents factor-s paran
.k pca corr-elations corr-elate eigen-values fapara eigen-vectors
.k graph-s graph-ics graph-ing
.x
	Q2/09	@browser:http://www.stata-journal.com/article.html?article=st0166!SJ 9(2):291--298@
	presents ^paran^, which permits classical parallel
	analysis and extensions to it for the @pca@ and @factor@
	commands

.e SJ-9-2 @net: sj 9-2 st0167!st0167@
.c sj
.a M. Chatfield and A. Mander
.t Skillings-Mack test (Friedman test when data are missing)
.k stat-istics skillings-mack mack test-s test-ing friedman miss-ing data-sets
.k set-s skilmack block-s design-s distrib-utions bal-anced rand-om
.k unbal-anced equal-ity rank-s tie-s
.o @skilmack@ if installed
.x
	Q2/09	@browser:http://www.stata-journal.com/article.html?article=st0167!SJ 9(2):299--305@
	provides the Skillings-Mack test, a general Friedman-type
	test that can be used in almost any block design with an
	arbitrary missing-data structure

.e SJ-9-2 @net: sj 9-2 st0168!st0168@
.c sj
.a N. J. Cox
.t Speaking Stata: I. J. Good & quasi-Bayes smooth. of cat. freq.
.k stat-istics quasi bayes-ian smooth-ing cat-egorical freq-uencies est-imates
.k est-imation qsbayes-i pseudo prob-ability prob-abilities zero
.k samp-les samp-ling rand-om matr-ices matr-ix tab-ulate tab-ulations mata
.k effect-s immed-iate
.o @qsbayes@, @qsbayesi@ if installed
.x
	Q2/09	@browser:http://www.stata-journal.com/article.html?article=st0168!SJ 9(2):306--314@
	explains I. J. Good's idea of quasi-Bayes estimation or
	smoothing of categorical frequencies in a contingency
	table

.e SJ-9-2 gn0046
.c sj
.a A. Gelman
.t Statistician's perspective on ^Mostly Harmless Econometrics^
.k book-s text-s review stat-istics econ-ometrics teach-ing
.k book-store learn-ing angrist pischke
.x
	Q2/09	@browser:http://www.stata-journal.com/article.html?article=gn0046!SJ 9(2):315--320@				    (no commands)
	book review of ^Mostly Harmless Econometrics: An Empiricist's^
	^Companion^ by Joshua D. Angrist and Jorn-Steffen Pischke

.e SJ-9-2 gr0037
.c sj
.a N. J. Cox
.t Stata tip 76: Separating seasonal time series
.k stat-istics separ-ated season-ally seasonality time-series series vary-ing
.k tip graph-s graph-ing graph-ics plot-s trace scat-terplots tsline line-s
.k separ-ate
.x
	Q2/09	@browser:http://www.stata-journal.com/article.html?article=gr0037!SJ 9(2):321--326@				    (no commands)
	tip on separating seasonal time series

.e SJ-9-2 @net: sj 9-2 gr0033_1!gr0033_1@
.c sj
.a T. M. Palmer, J. L. Peters, A. J. Sutton, and S. G. Moreno
.t Contour-enhanced funnel plots for meta-analysis
.k graph-s graph-ing graph-ics contour-s enhanced funnel plot-s plot-ting
.k anal-ysis asym-metry sym-metry bias-es bias-ed confunnel publication
.k est-imates est-imation stat-istics signif-icant signif-icance bina-ry
.k out-comes metafunnel test-s metan meta-bias metatrim metamodbias
.k trim fill
.x
	(help @confunnel@ if installed)
	Q2/09	@browser:http://www.stata-journal.com/article.html?article=up0025!SJ 9(2):327@
	software update to ^confunnel^ to produce plots with
	shaded regions of statistical significance

.e SJ-9-2 @net: sj 9-2 sbe24_3!sbe24_3@
.c sj
.a Harris, Bradburn, Deeks, Harbord, Altman, and Sterne
.t ^metan^: fixed- and random-effects meta-analysis
.k stat-istics meta anal-ysis metan funnel fix-edi effect-s rand-om graph-s
.k graph-ing graph-ics est-imates est-imation model-s forest plot-s
.k pred-ictions pred-icted interv-als bina-ry data mantel-haenszel
.k haenszel meth-ods inv-erse inv-ersion variance-s peto display-ing
.k weight-ing weight-s weight-ed heterog-eneity calcul-ate calcul-ations
.k log-s ratio-s risk-s size two 2 tabl-es colu-mns strat-a strat-ified
.k group-s test-s test-ing study studies pool-ing bayes-ian zero cell-s
.k sample-s samp-ling continu-ous breslow day distrib-utions var-iables
.k result-s std err-ors stand-ard labbe
.x
	(help @funnel@, @labbe@, @metan@ if installed)
	Q2/09	@browser:http://www.stata-journal.com/article.html?article=up0025!SJ 9(2):327@
	^by()^ variables were being converted to string format and
	the predictive interval option ^rfdist^ had an error when
	used for nonratio measures; these problems are fixed

.e SJ-9-2 @net: sj 9-2 st0096_2!st0096_2@
.c sj
.a N. Orsini, R. Bellocco, and S. Greenland
.t GLS for trend estimation of summarized dose-response data
.k glst trend est-imation est-imates est-imators dose-s response-s data
.k gls general-ized least sq-uares meta anal-ysis reg-ressions epi-demiology
.k epi-demiological expos-ures risk-s odds ratio-s case-controls control-s
.k incid-ence rate-s cumul-ative weight-ed weight-s weight-ing linear log-s
.k model-s matr-ices matr-ix cov-ariances heterog-eneity effect-s fix-ed
.k conf-idence interv-als level-s stand-ard err-or rand-oms vec-tors corr-elate
.k corr-elations off diag-onals asymp-totic stat-istics
.o @glst@ if installed
.x
	Q2/09	@browser:http://www.stata-journal.com/article.html?article=up0025!SJ 9(2):327@
	update for ^glst^ that makes sure the dataset is sorted by
	the study identification variable when pooling multiple
	studies

.e SJ-9-2 @net: sj 9-2 st0143_2!st0143_2@
.c sj
.a T. Cornelissen
.t fit a linear model with two high-dimensional fixed effects
.k stat-istics felsdvreg fit-ting linear model-s two 2 high dimen-sional
.k multi-dimensional dim-ensions fix-ed effect-s design-s matr-ix matr-ices
.k est-imates est-imation limit-s limit-ed mem-ory data-sets set-s panel-s
.k transfo-rmations least sq-uares dum-my dum-mies var-iables lsdv mom-ent
.k algor-ithms solutions mata feilsdvj corr-elations norm-alization
.k reg-ressions felsdv_group
.o @felsdvreg@ if installed
.x
	Q2/09	@browser:http://www.stata-journal.com/article.html?article=up0025!SJ 9(2):327@
	bug fix for the ^grouponly^ option

.e SJ-9-2 @net: sj 9-2 st0152_1!st0152_1@
.c sj
.a M. Sinning, M. Hahn, and T. K. Bauer
.t The Blinder-Oaxaca decomposition for nonlinear reg. models
.k stat-istics decomp-osition non-linear linear reg-ressions model-s
.k diff-erences outcome-s var-iables group-s nldecompose discrete limit-ed
.k limit-s depend-ent std err-ors stand-ard compon-ents boot-strapped
.k est-imates est-imation coef-ficients ols ordinary least sq-uares
.k cond-itional pool-ing counterfactual vector-s prefix command-s compon-ents
.k sav-ed result-s synt-ax sav-ing indica-tor mean-s blinder oaxaca
.o @nldecompose@ if installed
.x
	Q2/09	@browser:http://www.stata-journal.com/article.html?article=up0025!SJ 9(2):327@
	calculation of sample means are now adjusted for the use
	of weights and ^svy^ commands

.e SJ-9-1 @net: sj 9-1 st0154!st0154@
.c sj
.a M. S. Pepe, G. Longton, and H. Janes
.t Estimation and comparison of ROC curves
.k stat-istics est-imates est-imation compar-isons roc receiver-s operating
.k character-istics curv-es nonpar-ametric non param-etric est-imators
.k inv-erse reg-ressions discrim-inatory discrim-ination mark-ers mark-s
.k test-s test-ing comproc roccurve percent-iles value-s cumul-ative
.k distrib-utions control-s reference stand-ard stand-ardization stand-ardized
.k stand-ardisation func-tions sample-s samp-ling variability graph-s
.k graph-ing graph-ics method-s empir-ical norm-al covariate-s adjust-ed
.k synt-ax sav-ed result-s indic-es area partial index under auc summ-ary
.k summ-arize
.x
	(help @comproc@, @roccurve@ if installed)
	Q1/09	@browser:http://www.stata-journal.com/article.html?article=st0154!SJ 9(1):1--16@
	comprehensive suite of commands for performing ROC analysis

.e SJ-9-1 @net: sj 9-1 st0155!st0155@
.c sj
.a H. Janes, G. Longton, and M. S. Pepe
.t Accommodating covariates in ROC analysis
.k stat-istics covariate-s roc receiver-s operating character-istics curv-es
.k anal-ysis classif-ications classif-ied accur-acy mark-ers mark-s
.k diagnos-tics test-s test-ing factor-s obs-ervations adjust-ed
.k discrim-inatory discrim-ination summ-ary summ-arize stand-ard
.k stand-ardization stand-ardized stand-ardisation control-s distrib-utions
.k comproc roccurve rocreg cumul-ative func-tions percent-iles value-s
.k est-imates est-imation param-etric synt-ax calcul-ate calcul-ations
.k sample-s samp-ling variability index indic-es area under auc compar-isons
.k reg-ressions model-s param-eters evaluation-s increment-s linear
.k pred-ictions pred-icted
.x
	(help @comproc@, @roccurve@, @rocreg@ if installed)
	Q1/09	@browser:http://www.stata-journal.com/article.html?article=st0155!SJ 9(1):17--39@
	describes three ways of incorporating covariate information
	in an ROC analysis

.e SJ-9-1 @net: sj 9-1 st0156!st0156@
.c sj
.a I. R. White
.t Multivariate random-effects meta-analysis
.k stat-istics multiv-ariate rand-om effect-s meta anal-ysis param-eters
.k mult-iple outcome-s compar-isons compar-e group-s mvmeta mvmeta_l max-imum
.k like-lihood restric-ted restric-tions method-s of mom-ents est-imates
.k est-imation model-s mvmeta_make ml-e reml metareg newton-raphson raphson
.k synt-ax opt-ions nota-tion variance-s sav-ed result-s between study studies
.k covariate-s cov-ariances util-ity univar-iate heterog-eneity perfect
.k pred-ictions separ-ate reg-ressions augment-ed matr-ix matr-ices
.o @mvmeta@, @mvmeta_make@, if installed
.x
	Q1/09	@browser:http://www.stata-journal.com/article.html?article=st0156!SJ 9(1):40--56@
	maximum likelihood, restricted maximum likelihood, or
	method-of-moments estimation of random-effects multivariate
	meta-analysis models

.e SJ-9-1 @net: sj 9-1 st0157!st0157@
.c sj
.a I. R. White and J. P. T. Higgins
.t Meta-analysis with missing data
.k stat-istics meta anal-ysis miss-ing data-sets set-s metamiss bina-ry
.k outcome-s value-s rand-om bias odd-s ratio-s succ-ess fail-ure metan
.k bayes-ian synt-ax simple imput-e imput-ing imput-ation prior specifica-tion
.k specifici-ty arg-uments specify opt-ions obs-ervations sav-ed result-s
.k case-s zero cell-s count-s
.o @metamiss@ if installed
.x
	Q1/09	@browser:http://www.stata-journal.com/article.html?article=st0157!SJ 9(1):57--69@
	meta-analysis with binary outcomes when some or all studies
	have missing data

.e SJ-9-1 @net: sj 9-1 st0158!st0158@
.c sj
.a J. Kaiser and M. G. Lacy
.t A general-purpose method for two-group randomization tests
.k stat-istics general-ized method-s two-group group-s rand-om rand-omization
.k test-s test-ing calcul-ate calcul-ator calcul-ations exact p level-s
.k sample-s samp-ling signif-icant signif-icance somer-sd d tsrtest mwtest
.k fptest somersdtest cvtest vartest hyp-othesis hyp-otheses null p-values
.k algor-ithms efficient permu-tation flex-ible permute comb-inations
.k var-iables comb-inatorial synt-ax arg-uments opt-ions sav-ed result-s
.k diff-erences relativ-e variation coef-ficients multin-omial ranksamplediff
.k samplediff somd sddiff
.x
	(help @fptest@, @mwtest@, @somersdtest@, @tsrtest@,
	@vartest@ if installed)
	Q1/09	@browser:http://www.stata-journal.com/article.html?article=st0158!SJ 9(1):70--85@
	outlines an approach to calculate exact p-levels for two-
	sample randomization tests

.e SJ-9-1 @net: sj 9-1 st0159!st0159@
.c sj
.a D. Roodman
.t How to do ^xtabond2^: An intro. to difference and system GMM
.k stat-istics xt-abond2 intro-duction diff-erences system-s gmm general-ized
.k meth-ods mom-ents est-imators est-imates est-imation linear limited
.k time-spans span-s fix-ed effect-s endog-enous reg-ressors arellano bond
.k test-s test-ing autocor-relations corr-elations panel-s period-s collapse
.k instrum-ental reg-ressions ols ordinary least sq-uares efficient vec-tors
.k feasible weight-ing weight-s matr-ix matr-ices stand-ard err-ors variance-s
.k sargan hansen overident-ification restric-ted restric-tions exog-enous
.k two-stage stage 2 validity var-iables lag-s transfo-rmations anderson hsiao
.k iv-regress depend-ent 2sls dynamic orthog-onal deviation one-way step monte
.k carlo simul-ations serial-ly synt-ax abar obs-ervations samp-les samp-ling
.k frequent-ly freq-uency xtab2_p
.o @xtabond2@ if installed
.x
	Q1/09	@browser:http://www.stata-journal.com/article.html?article=st0159!SJ 9(1):86--136@
	introduces linear GMM; describes how limited time span
	and potential for fixed effects and endogenous regressors
	drive the design of estimators; shows how to apply
	difference and system GMM estimators with ^xtabond2^

.e SJ-9-1 @net:sj 9-1 pr0046!pr0046@
.c sj
.a N. J. Cox
.t Speaking Stata: Rowwise
.k prog-ramming prog-rams row-s colu-mns obs-ervations egen func-tions
.k loop-ing loop-s mata matr-ix matr-ices vector-s rowsort rowranks data-sets
.k set-s var-iables rowwise oper-ators max-imum min-imums forvalues
.k unab-breviate abbrev-iations abbrev-iate macro-s local-ly list-s inlist
.k comma-s separ-ated miss-ing quietly value-s nonmiss-ing any all count-s
.k med-ians num-eric num-bers distinct str-ings sort-ing rank-s
.k rank-ings ascend-ing descend-ing opt-ions synt-ax
.o @rowsort@, @rowranks@ if installed
.x
	Q1/09	@browser:http://www.stata-journal.com/article.html?article=pr0046!SJ 9(1):137--157@
	shows how to exploit functions, @egen@ functions, and Mata
	for working rowwise; ^rowsort^ and ^rowranks^ are introduced

.e SJ-9-1 gn0044
.c sj
.a A. C. Acock
.t Review of ^The Workflow of Data Analysis Using Stata^
.k book-s text-s review stat-istics workflow anal-ysis data-sets set-s
.k long manage-ment
.x
	Q1/09	@browser:http://www.stata-journal.com/article.html?article=gn0044!SJ 9(1):158--160@				    (no commands)
	book review of ^The Workflow of Data Analysis Using Stata^,
	by J. Scott Long

.e SJ-9-1 st0160
.c sj
.a C. F. Baum and T. Linz
.t Evaluating concavity for production and cost functions
.k stat-istics evaluation-s eval-uators production func-tions cost-s share-d
.k eq-uations est-imates est-imation sureg seemingly unrel-ated reg-ressions
.k factor-s matr-ix matr-ices eigen-values
.x
	Q1/09	@browser:http://www.stata-journal.com/article.html?article=st0160!SJ 9(1):161--165@				    (no commands)
	discusses how to evaluate production and cost functions

.e SJ-9-1 dm0044
.c sj
.a C. F. Baum
.t Stata tip 73: @append@ with care!
.k tip data-sets set-s manage-ment append merge comb-ine join var-iables
.k str-ings num-erical
.x
	Q1/09	@browser:http://www.stata-journal.com/article.html?article=dm0044!SJ 9(1):166--168@				    (no commands)
	tip on how to @append@ datasets with care

.e SJ-9-1 st0161
.c sj
.a R. G. Gutierrez and P. A. Lachenbruch
.t Stata tip 74: ^firstonly^, a new option for @tab2@
.k tip stat-istics first-only opt-ions
.k tab2 cat-egorical var-iables conting-ency tabl-es
.x
	Q1/09	@browser:http://www.stata-journal.com/article.html?article=st0161!SJ 9(1):169--170@				    (no commands)
	tip introducing new option ^firstonly^ for @tab2@

.e SJ-9-1 gn0045
.c sj
.a K. Crow
.t Stata tip 75: Setting up Stata for a presentation
.k tip set-s set-tings stata change sav-ed sav-ing manip-ulation max-imization
.k win-dows font-s pref-erences size style-s
.x
	Q1/09	@browser:http://www.stata-journal.com/article.html?article=gn0045!SJ 9(1):171--172@				    (no commands)
	tip on how to set up Stata for a presentation

.e SJ-9-1 @net:sj 9-1 sbe22_1!sbe22_1@
.c stb
.t Cumulative meta analysis
.a J. Sterne
.k stat-istics meta anal-ysis cumul-ative metacum metacum_examples
.o @metacum@ if installed
.x
	Q1/09	@browser:http://www.stata-journal.com/article.html?article=up0024!SJ 9(1):173@
	software update to allow ^metacum^ to work with modern
	graphics and to use the same syntax as @metan@

.e SJ-9-1 @net: sj 9-1 st0096_1!st0096_1@
.c sj
.a N. Orsini, R. Bellocco, and S. Greenland
.t GLS for trend estimation of summarized dose-response data
.k glst trend est-imation est-imates est-imators dose-s response-s data
.k gls general-ized least sq-uares meta anal-ysis reg-ressions epi-demiology
.k epi-demiological expos-ures risk-s odds ratio-s case-controls control-s
.k incid-ence rate-s cumul-ative weight-ed weight-s weight-ing linear log-s
.k model-s matr-ices matr-ix cov-ariances heterog-eneity effect-s fix-ed
.k conf-idence interv-als level-s stand-ard err-or rand-oms vec-tors corr-elate
.k corr-elations off diag-onals asymp-totic stat-istics
.o @glst@ if installed
.x
	Q1/09	@browser:http://www.stata-journal.com/article.html?article=up0024!SJ 9(1):173@
	software update for ^glst^ that includes new options to
	investigate specific studies included in the dose-response
	meta-analysis

.e SJ-9-1 @net: sj 9-1 st0143_1!st0143_1@
.c sj
.a T. Cornelissen
.t fit a linear model with two high-dimensional fixed effects
.k stat-istics felsdvreg fit-ting linear model-s two 2 high dimen-sional
.k multi-dimensional dim-ensions fix-ed effect-s design-s matr-ix matr-ices
.k est-imates est-imation limit-s limit-ed mem-ory data-sets set-s panel-s
.k transfo-rmations least sq-uares dum-my dum-mies var-iables lsdv mom-ent
.k algor-ithms solutions mata feilsdvj corr-elations norm-alization
.k reg-ressions felsdv_group
.o @felsdvreg@ if installed
.x
	Q1/09	@browser:http://www.stata-journal.com/article.html?article=up0024!SJ 9(1):173@
	software update for the ^felsdvreg^ command that allows
	F tests to be optional, making ^felsdvreg^ more efficient

.e SJ-8-4 @net: sj 8-4 st0151!st0151@
.c sj
.a B. Jann
.t The Blinder-Oaxaca decomposition for linear reg. models
.k stat-istics decomp-osition mean-s outcome-s diff-erences group-s gap-s
.k oaxaca linear reg-ressions model-s counterfactual var-iables cat-egorical
.k pred-ictors est-imates est-imation std err-ors stand-ard coef-ficients
.k compon-ents param-eters vector-s indica-tor samp-les samp-ling variance-s
.k infer-ence est-imators variation reg-ressors matr-ix matr-ices
.k transfo-rmations transfo-rmed pool-ing delta method-s svy survey-s svyset
.k exp-onential exp-onentiation exp-onentiated result-s weight-s bias
.k adjust-ed selec-tion blinder _oaxaca
.o @oaxaca@ if installed
.x
	Q4/08	@browser:http://www.stata-journal.com/article.html?article=st0151!SJ 8(4):453--479@
	implements the Blinder-Oaxaca decomposition, which is often
	used to study mean outcome differences between groups

.e SJ-8-4 @net: sj 8-4 st0152!st0152@
.c sj
.a M. Sinning, M. Hahn, and T. K. Bauer
.t The Blinder-Oaxaca decomposition for nonlinear reg. models
.k stat-istics decomp-osition non-linear linear reg-ressions model-s
.k diff-erences outcome-s var-iables group-s nldecompose discrete limit-ed
.k limit-s depend-ent std err-ors stand-ard compon-ents boot-strapped
.k est-imates est-imation coef-ficients ols ordinary least sq-uares
.k cond-itional pool-ing counterfactual vector-s prefix command-s compon-ents
.k sav-ed result-s synt-ax sav-ing indica-tor mean-s blinder oaxaca
.o @nldecompose@ if installed
.x
	Q4/08	@browser:http://www.stata-journal.com/article.html?article=st0152!SJ 8(4):480--492@
	implements a general Blinder-Oaxaca decomposition for
	nonlinear models

.e SJ-8-4 @net: sj 8-4 sbe23_1!sbe23_1@
.c sj
.a R. M. Harbord and J. P. T. Higgins
.t Meta-regression in Stata
.k stat-istics meta anal-ysis reg-ressions metareg study studies level
.k summ-ary data-sets set-s est-imates est-imation method-s permu-tation
.k test-s test-ing p-values value-s graph-s graph-ing graph-ics pred-ictions
.k pred-icted heterog-eneity result-s mult-iple variance-s ml-e max-imum
.k like-lihood reml restric-ted restric-tions std err-ors stand-ard
.k conf-idence interv-als output-ting output-ing rand-om fix-ed effect-s
.k linear pred-ictor resid-uals covariate-s metan bina-ry log-s odd-s ratio-s
.k risk-s size calcul-ate post-estimations algor-ithms t-tests variation
.k between adjust-ed r-squared r-2 sq-uared joint fit-ting fit-s fit-ted
.k model-s monte carlo simul-ations permute line-s bayes-ian plot-s
.k sav-ed sav-ing formula mom-ents knapp hartung
.k metareg_ll metareg_p metareg_pm
.o @metareg@ if installed
.x
	Q4/08	@browser:http://www.stata-journal.com/article.html?article=sbe23_1!SJ 8(4):493--519@
	presents a revised version of the ^metareg^ command, which
	performs meta-analysis regression on study-level summary
	data

.e SJ-8-4 st0153
.c sj
.a B. T. West, P. Berglund, and S. G. Heeringa
.t An examination of subpop. anal. of complex-sample svy data
.k stat-istics subpop-ulations anal-ysis complex sample-s survey-s data-sets
.k set-s design-s pop-ulations domain cond-itional calcul-ate degree-s freedom
.k df est-imates est-imation infer-ence simple rand-om obs-ervations
.k strat-ified size samp-ling strat-a strat-um clust-ers clust-ering psu
.k var-iables variance-s indica-tor svy std err-ors stand-ard conf-idence
.k interv-als test-s test-ing replic-ations repli-cates weight-ing weight-s
.x
	Q4/08	@browser:http://www.stata-journal.com/article.html?article=st0153!SJ 8(4):520--531@				    (no commands)
	considers two approaches that analysts of complex-sample
	survey data can follow when analyzing subpopulations and
	presents examples of each approach

.e SJ-8-4 st0136_1
.c sj
.a A. Nichols
.t Erratum and discussion of propensity-score reweighting
.k stat-istics caus-al infer-ence obs-ervations data-sets set-s manage-ment
.k est-imates est-imation param-eters panel-s reg-ressions match-ing
.k instrum-ental var-iables discon-tinuities xt-reg psmatch2 nnmatch iv-reg2
.k iv-regress lpoly xt-overid propensity scor-es weak identifier-s
.k discon-tinuities local-ly poly-nomials treat-ments effect-s ordinary
.k method-s est-imators iv design-s model-s confound-ing ave-rages rubin-s
.k stable stabil-ity unit-s value-s assump-tions omit-ted bias-es bias-ed
.k selec-tion endog-enous endogeneity sensitiv-ity test-s test-ing system-s
.k equation-s group-s marginal linear fix-ed least sq-uares sq-uared ols
.k first diff-erences long clus-ters clus-tering clus-tered robust
.k rand-om indica-tor nearest neighbor-s bina-ry pscore sensatt mhbounds
.k decomp-osition error-s validity exog-enous two-stage stage 2 exclusion
.k restric-ted restric-tions reg-ressors specifica-tion reset overid
.k ivendog func-tional form-s std stand-ard err-ors wald dens-ity continu-ous
.k kdensity kern-el
.x
	Q4/08	@browser:http://www.stata-journal.com/article.html?article=st0136_1!SJ 8(4):532--539@				      (no commands)
	discusses propensity-score reweighting

.e SJ-8-4 @net: sj 8-4 dm0041!dm0041@
.c sj
.a W. Vanlaar
.t A shortcut through long loops: alter. to looping over obs.
.k data-sets set-s manage-ment long loop-ing loop-s obs-ervations merge
.k comb-ine join mapch append index key-s identifier-s var-iables format-s
.k format-ting format-ted refer-ence cross-reference sort chain-ed map-ping
.k repeat-ing result-s noise repli-cates manip-ulation drop-ped drop-ping
.k erase delete output-ting output-ing match temp-orary file-s replace
.k change event
.o @mapch@ if installed
.x
	Q4/08	@browser:http://www.stata-journal.com/article.html?article=dm0041!SJ 8(4):540--553@
	discusses two alternative solutions to looping over
	observations that can be used to overcome a particular
	data-management problem of merging datasets in which
	unique key identifiers changed over time

.e SJ-8-4 @net:sj 8-4 st0029_1!st0029_1@
.c sj
.a B. P. Poi
.t Demand-system estimation: Update
.k stat-istics est-imation max-imum like-lihood demand eq-uations non linear
.k nonlin-ear quaids lnl_quaids quaids_delta quaids_params quaids_vec vec_sum
.k system nlsur general-ized least sq-uares prog-ramming prog-rams func-tions
.k eval-uators nlcom nlsurquaids
.x
	Q4/08	@browser:http://www.stata-journal.com/article.html?article=st0029_1!SJ 8(4):554--556@
	example of how to estimate systems of household
	demand equations; techniques for estimating any system of
	nonlinear equations using @nlusr@ instead of @ml@

.e SJ-8-4 @net:sj 8-4 dm0042!dm0042@
.c sj
.a N. J. Cox and G. M. Longton
.t Speaking Stata: Distinct observations
.k data-sets set-s manage-ment distinct obs-ervations var-iables by: : egen
.k unique check-s check-ing value-s dup-licates contract reduce inspect code-s
.k book-s codebook isid tab-ulate level-s levelsof num-erical num-bers
.k str-ings count-s sort replace miss-ing
.o @distinct@ if installed
.x
	Q4/08	@browser:http://www.stata-journal.com/article.html?article=dm0042!SJ 8(4):557--568@
	shows how to answer questions about distinct observations
	from first principles; provides a convenience command

.e SJ-8-4 gn0041
.c sj
.a A. Terracol
.t Review of ^Stata par la pratique^
.k book-s text-s review french stat-istics prog-ramming prog-rams graph-ics
.k graph-ing graph-s cahuzac bontemps
.x
	Q4/08	@browser:http://www.stata-journal.com/article.html?article=gn0041!SJ 8(4):569--573@				    (no commands)
	book review (in English) of ^Stata par la pratique:^
	^statistiques, graphiques et elements de programmation^,
	by Eric Cahuzac and Christophe Bontemps

.e SJ-8-4 gn0042
.c sj
.a A. Terracol
.t Review of ^Stata par la pratique^
.k book-s text-s review french stat-istics prog-ramming prog-rams graph-ics
.k graph-ing graph-s cahuzac bontemps
.x
	Q4/08	@browser:http://www.stata-journal.com/article.html?article=gn0042!SJ 8(4):574--578@				    (no commands)
	book review (in French) of ^Stata par la pratique:^
	^statistiques, graphiques et elements de programmation^,
	by Eric Cahuzac and Christophe Bontemps

.e SJ-8-4 gn0043
.c sj
.a N. J. Horton
.t Review of ^Multilevel & Long. Modeling Using Stata, 2nd Ed^
.k book-s text-s review rabe-hesketh hesketh skrondal
.k gen-eralized linear latent model-s model-ing multi-level level rand-om
.k effect-s gllamm glvm longi-tudinal longi-tudinal norm-ally distrib-utions
.k distrib-uted bina-ry ordinal count-s nest-ed cross variance-s compon-ents
.k clus-ters clus-tering clus-tered xt-mixed intercep-t logis-tic est-imation
.k est-imates reg-ressions outcome-s probit order-ed poisson count-s data-sets
.k set-s continu-ous
.x
	Q4/08	@browser:http://www.stata-journal.com/article.html?article=gn0043!SJ 8(4):579--582@				    (no commands)
	book review of ^Multilevel and Longitudinal Modeling^
	^Using Stata, 2nd Edition^ by Rabe-Hesketh and Skrondal

.e SJ-8-4 pr0044
.c sj
.a A. R. Riley
.t Tip 69: Producing log files based on interactive commands
.k tip prog-ramming prog-rams production log-s file-s interact-ions
.k interact-ively command-s edit-ors review-s win-dows histor-y do-files
.k sequen-tial seq-uences num-bers return code-s result-s error-s sav-ed
.k selec-tion cmdlog
.x
	Q4/08	@browser:http://www.stata-journal.com/article.html?article=pr0044!SJ 8(4):583--585@				    (no commands)
	tip how to produce log files based on successful
	interactive commands

.e SJ-8-4 pr0045
.c sj
.a N. J. Cox
.t Stata tip 70: Beware the evaluating equal sign
.k tip prog-ramming prog-rams evaluation-s equal-ity = equal-s macro-s
.k local-ly global-ly expr-essions str-ings limit-s result-s length
.x
	Q4/08	@browser:http://www.stata-journal.com/article.html?article=pr0045!SJ 8(4):586--587@				    (no commands)
	tip explaining the pitfall of losing content in a macro
	because of limits on the length of string expressions

.e SJ-8-4 dm0043
.c sj
.a N. J. Cox
.t Tip 71: The problem of split identity, or how to group dyads
.k tip prog-ramming prog-rams data-sets set-s manage-ment split mult-iple
.k identity group-s identifier-s dyad var-iables str-ings obs-ervations
.k num-eric num-bers arg-uments
.x
	Q4/08	@browser:http://www.stata-journal.com/article.html?article=dm0043!SJ 8(4):588--591@				    (no commands)
	tip on how to handle dyadic identifiers

.e SJ-8-4 gr0036
.c sj
.a K. Crow
.t Tip 72: Using Graph Recorder to create pseudograph schemes
.k tip graph-s graph-ing graph-ics record-s create pseudo scheme-s edit-ors
.k play file-s sav-ed
.x
	Q4/08	@browser:http://www.stata-journal.com/article.html?article=gr0036!SJ 8(4):592--593@				    (no commands)
	tip on how to use the Graph Recorder to create a
	pseudograph scheme

.e SJ-8-4 @net:sj 8-4 dm89_1!dm89_1@
.c sj
.a N. J. Cox
.t Dropping variables or observations with missing values
.k data-sets set-s manage-ment miss-ing value-s drop-ping var-iables
.k obs-ervations dropmiss
.o @dropmiss@ if installed
.x
	Q4/08	@browser:http://www.stata-journal.com/article.html?article=up0023!SJ 8(4):594@
	update in style and content; added a new ^force^ option

.e SJ-8-4 @net:sj 8-4 gr0024_1!gr0024_1@
.c sj
.a F. M.-S. Barthel and P. Royston
.t Graphical representation of interactions
.k graph-s graph-ics graph-ing
.k fintplot-k fintplot-kcox fintplot-klog fintplot-log fintmenu
.k interact-ions forest plot-s rand-omized control-led trial-s
.k surviv-al anal-ysis logis-tic logit reg-ressions
.k cox propor-tional haz-ards model-s
.o @fintplot@ if installed
.x
	Q4/08	@browser:http://www.stata-journal.com/article.html?article=up0023!SJ 8(4):594@
	fixed bug causing an error in the calculation of the hazard
	ratio or relative risk of treatment for the second level of
	the covariate alone

.e SJ-8-4 @net: sj 8-4 st0015_5!st0015_5@
.c sj
.a T. J. Steichen and N. J. Cox
.t Software update for ^concord^
.k stat-istics concord-ance corr-elations coef-ficients lin graph-s graph-ics
.k limit-s agree-ment meas-urements compar-isons
.o @concord@ if installed
.x
	Q4/08	@browser:http://www.stata-journal.com/article.html?article=up0023!SJ 8(4):594@
	dialog box modified to correct visual layout problems

.e SJ-8-4 @net: sj 8-4 st0100_1!st0100_1@
.c sj
.a A. Lopez-Feldman
.t Decomposing inequality and obtaining marginal effects
.k descogini stat-istics gini decomp-osition income source inequal-ity
.k stand-ard err-ors conf-idence interv-als boot-strapped marginal effect-s
.o @descogini@ if installed
.x
	Q4/08	@browser:http://www.stata-journal.com/article.html?article=up0023!SJ 8(4):594@
	bugs have been fixed to avoid problems in the estimation
	of marginal effects as well as the unintended deletion of
	variables from users' data

.e SJ-8-4 @net: sj 8-4 st0150_1!st0150_1@
.c sj
.a M. Bia and A. Mattei
.t The dose-response function adj. for the gen. propensity score
.k stat-istics est-imation est-imates dose-s response-s func-tions adjust-ed
.k general-ized propensity scor-es continu-ous treat-ments gpscore
.k doseresponse model-s est-imators bina-ry anal-ysis confound-ing caus-al
.k effect-s outcome-s weak infer-ence cond-itional distrib-utions cov-ariances
.k covariate-s var-iables bal-anced effect-s reg-ressions boot-strapped
.k bias-ed output-ting output-ing doseresponse_model gpscore_model
.o @doseresponse@, @gpscore@ if installed
.x
	Q4/08	@browser:http://www.stata-journal.com/article.html?article=up0023!SJ 8(4):594@
	improved handling of predicted probabilities; correction
	of some references to variables named ^treatment_level_plus^
	or similar

.e SJ-8-4 @net:sj 8-4 sxd1_4!sxd1_4@
.c sj
.a P. Ryan
.t Random allocation of treatments in blocks
.k stat-istics ralloc rct-s rand-omized control-led trial-s rand-omization
.k block-ed block-ing strat-ified factori-al design-s crossover switchback
.k alloc-ation treat-ments block-s
.o @ralloc@ if installed
.x
	Q4/08	@browser:http://www.stata-journal.com/article.html?article=up0023!SJ 8(4):594@
	correction of a bug causing graceless exits for Stata/SE
	and Stata/MP users

.e SJ-8-3 @net: sj 8-3 st0148!st0148@
.c sj
.a Y.V. Marchenko, R.J. Carroll, D.Y. Lin, C.I. Amos, and R.G. Gutierrez
.t Semiparametric analysis of case-control genetic data
.k stat-istics method-s semi-nonparametric non param-etric anal-ysis
.k case-controls control-s data-sets set-s environ-ment factor-s haplotype-s
.k haplologit genotype-s hardy weinberg equilib-rium gene-tics indep-endence
.k indep-endent like-lihood logis-tic reg-ressions covariate-s distrib-utions
.k profile interact-ions miss-ing func-tions log-s max-imum max-imization
.k est-imates est-imation risk-s inherit-ance effect-s simul-ations
.k _gntp2dptp _haplo_em_phased _haplologit_d1_rare-x
.k snp sing-le nucleo-tide polymorph-ism
.x
	(@haplologit@ if installed)
	Q3/08	@browser:http://www.stata-journal.com/article.html?article=st0148!SJ 8(3):305--333@
	implements efficient profile-likelihood semiparametric
	methods for fitting gene-environment models in the special
	cases of a rare disease, a single candidate gene in Hardy-
	Weinberg equilibrium, and independence of genetic and
	environmental factors

.e SJ-8-3 @net: sj 8-3 st0149!st0149@
.c sj
.a R. Emsley, M. Lunt, A. Pickles, and G. Dunn
.t Implementing double-robust estimators of causal effects
.k stat-istics double-s robust est-imates est-imation est-imators caus-al
.k effect-s dr selec-tion monte carlo simul-ations model-s confound-ing
.k obs-ervations data-sets set-s param-eters expos-ures risk-s reg-ressions
.k method-s inv-erse prob-abilities prob-ability weight-ing weight-s
.k propensity scor-es match-ing strat-ified strat-ification treat-ments
.k outcome-s nota-tion pred-ictions pred-icted baseline value-s group-s
.k var-iables bina-ry logis-tic boot-strapped std err-ors stand-ard
.o @dr@ if installed
.x
	Q3/08	@browser:http://www.stata-journal.com/article.html?article=st0149!SJ 8(3):334--353@
	presents a double-robust estimator for pretest-posttest
	studies

.e SJ-8-3 @net: sj 8-3 st0150!st0150@
.c sj
.a M. Bia and A. Mattei
.t The dose-response function adj. for the gen. propensity score
.k stat-istics est-imation est-imates dose-s response-s func-tions adjust-ed
.k general-ized propensity scor-es continu-ous treat-ments gpscore
.k doseresponse model-s est-imators bina-ry anal-ysis confound-ing caus-al
.k effect-s outcome-s weak infer-ence cond-itional distrib-utions cov-ariances
.k covariate-s var-iables bal-anced effect-s reg-ressions boot-strapped
.k bias-ed output-ting output-ing doseresponse_model gpscore_model
.o @doseresponse@, @gpscore@ if installed
.x
	Q3/08	@browser:http://www.stata-journal.com/article.html?article=st0150!SJ 8(3):354--373@
	estimates the propensity score with a continuous treatment,
	tests the balancing property of the generalized propensity
	score, and estimates the dose-response function

.e SJ-8-3 @net: sj 8-3 dm0037!dm0037@
.c sj
.a M. Lokshin and Z. Sajaia
.t Creating print-ready tables in Stata
.k data-sets set-s manage-ment creat-e creat-ed creat-ing print-ing tab-les
.k xml_tab xml .xml format-s tab-s est-imates est-imation matr-ix matr-ices
.k format-ting excel ms-word word result-s output-ting output-ing stor-e
.k gen-erate reg-ressions param-eters stat-istics coef-ficients mult-iple
.k eq-uations model-s marginal effect-s append expor-ting file-s
.o @xml_tab@ if installed
.x
	Q3/08	@browser:http://www.stata-journal.com/article.html?article=dm0037!SJ 8(3):374--389@
	outputs the results of estimation commands and Stata
	matrices directly into tables in XML format

.e SJ-8-3 @net: sj 8-3 dm0038!dm0038@
.c sj
.a R. Raciborski
.t kountry: Merging cross-country data from multiple sources
.k data-sets set-s manage-ment kountry kountryadd kountrybackup kountryrestore
.k util-ity merge comb-ine cross mult-iple source translate convert
.k convers-ions code-s scheme-s recode stand-ard stand-ardization
.k stand-ardized stand-ardisation stand-ardised form-s gen-erate
.k geograph-ically region-s var-iables name-s country
.k kountryregion-s k_capc k_cowc k_cown k_geo_cow k_geo_marc k_geo_meb
.k k_geo_men k_geo_sov k_geo_un-det k_imfn k_iso2c k_iso3c k_iso3n k_marc
.k k_mcc k_other k_stuck k_unc
.x
	(@kountry@, @kountryadd@, @kountrybackup@, @kountrynames@,
	@kountryregions@ if installed)
	Q3/08	@browser:http://www.stata-journal.com/article.html?article=dm0038!SJ 8(3):390--400@
	translates one country-coding scheme into another, recodes
	country names into a standardized form, and generates
	geographic-region variables

.e SJ-8-3 pr0040
.c sj
.a W. Gould
.t Mata Matters: Macros
.k prog-ramming prog-rams mata matr-ix lang-uage macro-s ado-files file-s
.k var-iables loop-ing loop-s hold num-eric num-bers str-ings value-s
.k general-ized interface scal-ars local-ly global-ly func-tions code-s
.k compile
.x
	Q3/08	@browser:http://www.stata-journal.com/article.html?article=pr0040!SJ 8(3):401--412@				    (no commands)
	describes why macros are seldom needed in Mata and
	outlines what you might do with macros in Mata

.e SJ-8-3 @net: sj 8-3 pr0041!pr0041@
.c sj
.a N. J. Cox
.t Speaking Stata: Corr. with confidence, Fisher's z revisited
.k stat-istics prog-ramming prog-rams corr-elations conf-idence fisher-s z
.k transfo-rmations inv-erse hyperbol-ic tan-gent tanh func-tions corrci-i
.k interv-als matr-ix matr-ices multiv-ariate anal-ysis mata
.k boot-strapped pearson-s bivar-iate norm-al atan-h sinh cosh sin-e cos-ine
.k trig-onometric exp-onential odd-s arc tan-gent arctan-gent bias correct-ion
.k correct-ed prob-abilities prob-ability plot-s plot-ting sample-s samp-ling
.k distrib-utions efron num-bers num-eric var-iables miss-ing value-s
.k immed-iate
.o @corrci@, @corrcii@ if installed
.x
	Q3/08	@browser:http://www.stata-journal.com/article.html?article=pr0041!SJ 8(3):413--439@
	reviews Fisher's z transformation and its inverse, the
	hyperbolic tangent, and reviews their use in inference
	with correlations

.e SJ-8-3 gn0040
.c sj
.a S. Merryman
.t Review of ^A Visual Guide to Stata Graphics, Second Edition^
.k book-s text-s review mitchell graph-ics graph-ing graph-s plot-s stata
.k lang-uage edit-ors visual
.x
	Q3/08	@browser:http://www.stata-journal.com/article.html?article=gn0040!SJ 8(3):440--443@				    (no commands)
	book review of ^A Visual Guide to Stata Graphics,^
	^Second Edition^ by Mitchell (2008)

.e SJ-8-3 dm0039
.c sj
.a J. Herrin and E. Poen
.t Stata tip 64: Cleaning up user-entered string variables
.k tip data-sets set-s manage-ment user-s enter-ing str-ings var-iables name-s
.k func-tions merge substitut-ion subinstr
.x
	Q3/08	@browser:http://www.stata-journal.com/article.html?article=dm0039!SJ 8(3):444--445@				    (no commands)
	tip on how to clean up user-entered string variables

.e SJ-8-3 pr0042
.c sj
.a N. J. Cox
.t Stata tip 65: Beware the backstabbing backslash
.k tip prog-ramming prog-rams backslash win-dows separ-ate esc-ape
.k substitut-ion subinstr
.x
	Q3/08	@browser:http://www.stata-journal.com/article.html?article=pr0042!SJ 8(3):446--447@				    (no commands)
	tip to use forward slash instead of backslash for
	directory and file names

.e SJ-8-3 dm0040
.c sj
.a M. Weiss
.t Stata tip 66: ^ds^--A hidden gem
.k tip data-sets set-s manage-ment ds command-s undocumented descrip-tions
.k describ-e var-iables
.x
	Q3/08	@browser:http://www.stata-journal.com/article.html?article=dm0040!SJ 8(3):448--449@				    (no commands)
	tip on how @ds@, an undocumented command, can identify
	subsets of variables with specified properties

.e SJ-8-3 pr0043
.c sj
.a N. J. Cox
.t Stata tip 67: ^J()^ now has greater replicating powers
.k tip prog-ramming prog-rams repli-cates replic-ations j func-tions mata
.k matr-ix matr-ices scal-ars vector-s
.x
	Q3/08	@browser:http://www.stata-journal.com/article.html?article=pr0043!SJ 8(3):450--451@				    (no commands)
	tip detailing @Mata J()@ function recent enhancements

.e SJ-8-3 @net:sj 8-3 st0123_1!st0123_1@
.c sj
.a R. Chiburis and M. Lokshin
.t ML and two-step estimation of ordered-probit selection model
.k stat-istics
.k max-imum like-lihood two-step step est-imation est-imates order-ed probit
.k selec-tion model-s reg-ressions oheckman monte carlo simul-ations bias
.k fiml info-rmation algor-ithms linear specifica-tion rule-s log-s
.k identify-ing problem-s d2 method-s ml-e pred-icted pred-ictions sav-ed
.k result-s examp-les data-sets gen-erate process-es baseline corr-elate
.k corr-elations err-ors mult-iple equation-s nonnorm-ality shoc-ks
.k exclusion restric-ted restric-tions
.o @oheckman@ if installed
.x
	Q3/08	@browser:http://www.stata-journal.com/article.html?article=up0022!SJ 8(3):452@
	bug fix for ^yif()^ option of ^oheckman^ causing ^predict^
	to fail

.e SJ-8-3 @net: sj 8-3 st0140_1!st0140_1@
.c sj
.a K. C. Longest and S. Vaisey
.t ^fuzzy^: prog. for performing qualitative comp. analyses (QCA)
.k stat-istics fuzzy prog-ramming prog-rams qualita-tive compar-isons compar-e
.k anal-ysis cmvom cnfgen coincid coverage fzplot
.k mavmb reduce setgen suffnec truthtab yavyb yvn yvo yvv yvy set-s
.k multiv-ariate data-sets boolean logit logic-al dicho-tomous
.k out-comes comb-inations cat-egorical
.k var-iables post-estimations est-imation est-imates command-s
.x
	(help @fuzzy@, @cmvom@, @cnfgen@, @coincid@, @coverage@, @fzplot@,
	@mavmb@, @reduce@, @setgen@, @suffnec@, @truthtab@, @yavyb@, @yvn@,
	@yvo@, @yvv@, @yvy@ if installed)
	Q3/08	@browser:http://www.stata-journal.com/article.html?article=up0022!SJ 8(3):452@
	minor fixes have been made to this package

.e SJ-8-2 @net: sj 8-2 st0142!st0142@
.c sj
.a B. Jann
.t Multinomial GOF: Large-sample svy & small-sample exact tests
.k stat-istics multin-omial goodness of fit gof samp-les samp-ling test-s
.k test-ing survey-s svy design-s correct-ed correct-ion exact large small
.k mgof mgofi dist-ributed cat-egorical var-iables monte carlo ksmirnov
.k kol-mogorov smir-nov chi-squared sq-uared chi-2 2 data-sets set-s discrete
.k null distrib-utions pearson-s like-lihoodratio ratio-s effect-s
.k propor-tional degree-s freedom df prob-abilities p-values value-s meth-ods
.k benford-s law
.o @mgof@ if installed
.x
	Q2/08	@browser:http://www.stata-journal.com/article.html?article=st0142!SJ 8(2):147--169@
	computes distributional tests for discrete (categorical,
	multinomial) variables and supports large-sample tests for
	complex survey designs and exact tests for small samples

.e SJ-8-2 @net: sj 8-2 st0143!st0143@
.c sj
.a T. Cornelissen
.t fit a linear model with two high-dimensional fixed effects
.k stat-istics felsdvreg fit-ting linear model-s two 2 high dimen-sional
.k multi-dimensional dim-ensions fix-ed effect-s design-s matr-ix matr-ices
.k est-imates est-imation limit-s limit-ed mem-ory data-sets set-s panel-s
.k transfo-rmations least sq-uares dum-my dum-mies var-iables lsdv mom-ent
.k algor-ithms solutions mata feilsdvj corr-elations norm-alization
.k reg-ressions felsdv_group
.o @felsdvreg@ if installed
.x
	Q2/08	@browser:http://www.stata-journal.com/article.html?article=st0143!SJ 8(2):170--189@
	uses a memory-saving decomposition of the design matrix
	to facilitate the estimation of a linear model with two
	high-dimensional fixed effects

.e SJ-8-2 @net: sj 8-2 st0144!st0144@
.c sj
.a G. De Luca
.t SNP and SML est. of uni- and bivariate binary-choice models
.k stat-istics est-imates est-imation univar-iate bivar-iate bina-ry choice
.k model-s nonpar-ametric non param-etric semi-nonparametric max-imum
.k like-lihood monte carlo simul-ations snp snp_ll ml-e discrete param-eters
.k distrib-utions kern-el func-tions log-likelihood log-s indica-tor gauss-ian
.k corr-elations corr-elate probit dens-ity latent reg-ressions error-s
.k approx-imations pseudo-likelihoods prob-abilities prob-ability
.k snp2 snp2_ll snp2s snp2s_ll sample-s samp-ling selec-tion
.k sml sml_ll sml2s sml2s_ll skew-ness kurt-osis biprobit klein spady lee
.k heckprob coef-ficients drop-ping gaukern gaukern_biv gallant nychka
.o @sml@, @snp@ if installed
.x
	Q2/08	@browser:http://www.stata-journal.com/article.html?article=st0144!SJ 8(2):190--220@
	provides semi-nonparametric and semiparametric maximum
	likelihood estimators for univariate and bivariate
	binary-choice models

.e SJ-8-2 @net: sj 8-2 st0145!st0145@
.c sj
.a M. Yasar, R. Raciborski, and B. Poi
.t Production function est. using the Olley and Pakes method
.k stat-istics opreg production func-tions est-imates est-imation selec-tion
.k bias-es bias-ed simult-aneous param-etric semi-nonparametric param-eters
.k ordinary least sq-uares ols markov output-ting output-ing input-s
.k prob-abilities prob-ability panel-s var-iables time coef-ficients meas-ures
.k olley pakes levpet
.o @opreg@ if installed
.x
	Q2/08	@browser:http://www.stata-journal.com/article.html?article=st0145!SJ 8(2):221--231@
	provides reliable productivity measures from production
	function estimation by controlling for simultaneity and
	selection bias

.e SJ-8-2 @net: sj 8-2 st0146!st0146@
.c sj
.a D. Persyn and J. Westerlund
.t Error-correction-based cointegration tests for panel data
.k stat-istics error-s correct-ion correct-ed based coint-egration test-s
.k test-ing panel-s data-sets set-s xt-west time-series series dimen-sional
.k cross section-al resid-uals depend-ent depend-ence group-s mean-s
.k param-eters stand-ard std asymp-totic distrib-utions boot-strapped
.k westerlund
.o @xtwest@ if installed
.x
	Q2/08	@browser:http://www.stata-journal.com/article.html?article=st0146!SJ 8(2):232--241@
	implements the four error-correction-based panel
	cointegration tests developed by Westerlund

.e SJ-8-2 @net: sj 8-2 gr0033!gr0033@
.c sj
.a T. M. Palmer, J. L. Peters, A. J. Sutton, and S. G. Moreno
.t Contour-enhanced funnel plots for meta-analysis
.k graph-s graph-ing graph-ics contour-s enhanced funnel plot-s plot-ting
.k anal-ysis asym-metry sym-metry bias-es bias-ed confunnel publication
.k est-imates est-imation stat-istics signif-icant signif-icance bina-ry
.k out-comes metafunnel test-s metan meta-bias metatrim metamodbias
.k trim fill
.x
	(help @confunnel@ if installed)
	Q2/08	@browser:http://www.stata-journal.com/article.html?article=gr0033!SJ 8(2):242--254@
	provides contour-enhanced funnel plots for meta-analysis

.e SJ-8-2 pr0038
.c sj
.a J. M. Linhart
.t Mata Matters: Overflow, underflow & IEEE floating-point format
.k prog-ramming prog-rams mata matr-ix lang-uage float-s float-ing point
.k format-s format-ting num-bers num-eric store stand-ard double-s underflow
.k overflow maxdouble miss-ing value-s mindouble hex-adecimal precis-ion
.k smallestdouble denormal-ized display base digit-s single byte-s bina-ry
.k decim-al type-s bit-s 32-bits 64-bits bias-es bias-ed exp-onential
.k hex-dump dump frac-tional calcul-ate calcul-ations
.x
	Q2/08	@browser:http://www.stata-journal.com/article.html?article=pr0038!SJ 8(2):255--268@				    (no commands)
	focuses on underflow and overflow and details of how
	floating-point numbers are stored in the IEEE 754
	floating-point standard

.e SJ-8-2 @net: sj 8-2 gr0034!gr0034@
.c sj
.a N. J. Cox
.t Speaking Stata: Between tables and graphs
.k graph-s graph-ing graph-ics tabl-es dot-s cat-egorical axis axes bar-s
.k two-way way labmask seqvar label-s position-s chart-s box-es plot-s
.k plot-ting hbar hbox horizont-ally data-sets set-s entry value-s num-erical
.k num-bers var-iables egen gen-erate str-ings mark-ers mark-s symb-ols
.k point-s legend-s scale-s scat-terplots int-egers numlist-s list-s
.k drop-lines line-s gap-s
.o @labmask@, @seqvar@ if installed
.x
	Q2/08	@browser:http://www.stata-journal.com/article.html?article=gr0034!SJ 8(2):269--289@
	outlines techniques for producing table-like graphs

.e SJ-8-2 pr0039
.c sj
.a A. R. Riley
.t Stata tip 60: Fast and easy changes to files with ^filefilter^
.k tip
.k prog-ramming prog-rams change file-s filefilter global-ly edit-ing global-s
.k search replacem-ent replace sav-ed copy-ing read-ing writ-ten writ-e
.x
	Q2/08	@browser:http://www.stata-journal.com/article.html?article=pr0039!SJ 8(2):290--292@				    (no commands)
	tip on how to make changes to a file using the
	^filefilter^ command

.e SJ-8-2 dm0036
.c sj
.a N. J. Cox
.t Stata tip 61: Decimal commas in results output & data input
.k tip data-sets set-s manage-ment decim-al comma-s result-s out-puting
.k out-putting input-ting input-ing frac-tional period-s point-s separ-ate
.k destring
.x
	Q2/08	@browser:http://www.stata-journal.com/article.html?article=dm0036!SJ 8(2):293--294@				    (no commands)
	tip on using commas as decimal separators for output
	and input

.e SJ-8-2 gr0035
.c sj
.a N. J. Cox and N. L. M. Barlow
.t Stata tip 62: Plotting on reversed scales
.k tip graph-s graph-ing graph-ics plot-ting plot-s reverse-d scale-s axis axes
.k horizont-ally vert-ically cat-egorical bar-s dot-s two-way way legend-s
.x
	Q2/08	@browser:http://www.stata-journal.com/article.html?article=gr0035!SJ 8(2):295--298@				    (no commands)
	tip on how to reverse scales on a graph

.e SJ-8-2 st0147
.c sj
.a C. F. Baum
.t Stata tip 63: Modeling proportions
.k tip stat-istics model-s model-ing propor-tional propor-tions frac-tionally
.k linear reg-ressions transfo-rmations logit response-s var-iables
.k pred-ictions pred-icted invlogit logis-tic group-ed glogit general-ized
.k glm data-sets set-s
.x
	Q2/08	@browser:http://www.stata-journal.com/article.html?article=st0147!SJ 8(2):299--303@				    (no commands)
	tip on how to model a response variable that appears
	as a proportion or fraction

.e SJ-8-1 @net: sj 8-1 sbe24_2!sbe24_2@
.c sj
.a Harris, Bradburn, Deeks, Harbord, Altman, and Sterne
.t ^metan^: fixed- and random-effects meta-analysis
.k stat-istics meta anal-ysis metan funnel fix-edi effect-s rand-om graph-s
.k graph-ing graph-ics est-imates est-imation model-s forest plot-s
.k pred-ictions pred-icted interv-als bina-ry data mantel-haenszel
.k haenszel meth-ods inv-erse inv-ersion variance-s peto display-ing
.k weight-ing weight-s weight-ed heterog-eneity calcul-ate calcul-ations
.k log-s ratio-s risk-s size two 2 tabl-es colu-mns strat-a strat-ified
.k group-s test-s test-ing study studies pool-ing bayes-ian zero cell-s
.k sample-s samp-ling continu-ous breslow day distrib-utions var-iables
.k result-s std err-ors stand-ard labbe
.x
	(help @funnel@, @labbe@, @metan@ if installed)
	Q1/08	@browser:http://www.stata-journal.com/article.html?article=sbe24_2!SJ 8(1):3--28@
	update of meta-analysis command ^metan^ including modern
	graphics, the ability to meta-analyze precalculated
	effect estimates, and analyze subgroups

.e SJ-8-1 @net: sj 8-1 st0138!st0138@
.c sj
.a N. Orsini, R. Bellocco, M. Bottai, A. Wolk, and S. Greenland
.t Deterministic and probabilistic sensitivity analysis
.k stat-istics sensitiv-ity anal-ysis study studies epi-demiology
.k epi-demiological classif-ied classif-ications error-s selec-tion bias
.k confound-ing relativ-e risk-s prob-ability prob-abilities distrib-utions
.k param-eters episens-i expos-ures effect-s ratio-s rate-s odd-s ordinary
.k class-ical dens-ity monte carlo specifici-ty specifica-tion adjust-ed
.k immed-iate func-tions case-s factor-s simul-ations design-s format-s
.k format-ted graph-s graph-ing graph-ics hist-ograms
.k episens_mcsa_unc episens_mcsa_mie episens_mcsa_sel episens_mcsa_all
.x
	(help @episens@, @episensi@ if installed)
	Q1/08	@browser:http://www.stata-journal.com/article.html?article=st0138!SJ 8(1):29--48@
	A tool for deterministic and probabilistic sensitivity
	analysis of epidemiologic studies that adjusts the
	relative risk for exposure misclassification, selection
	bias, and an unmeasured confounder

.e SJ-8-1 @net: sj 8-1 st0139!st0139@
.c sj
.a J. B. Carlin, J. C. Galati, and P. Royston
.t New framework for managing and analyzing multiply imputed data
.k stat-istics manage-ment anal-ysis mult-iply mult-iple imput-e imput-ing
.k imput-ation miss-ing value-s data-sets set-s stack-ed vert-ically mim
.k ice micombine rand-om comb-ine store est-imates est-imation param-eters
.k post-estimations manip-ulation transfo-rmations reshape append merge
.k check-s replay propor-tions logis-tic mimstack
.x
	(help @mim@, @mimstack@ if installed)
	Q1/08	@browser:http://www.stata-journal.com/article.html?article=st0139!SJ 8(1):49--67@
	tools for performing analyses of an ensemble of datasets
	that include multiple copies of the original data with
	imputations of missing values, as required for the method
	of multiple imputation

.e SJ-8-1 @net: sj 8-1 sg164_1!sg164_1@
.c sj
.a W. Sosa-Escudero and A. K. Bera
.t Tests for unbal. error-comp. under local misspecification
.k stat-istics test-s test-ing unbal-anced error-s compon-ents model-s
.k xt-reg xt-test1 cross section-al time-series series longi-tudinal
.k lagrange multipli-er baltagi li
.k local-ly specifica-tion first order-ed serial-ly corr-elations rand-om
.k effect-s summ-arize ordinary ols least sq-uared sq-uares resid-uals
.k panel-s data-sets set-s rao scor-e scor-ing bal-anced linear breusch
.k pagan max-imum like-lihood ml-e
.o @xttest1@ if installed
.x
	Q1/08	@browser:http://www.stata-journal.com/article.html?article=sg164_1!SJ 8(1):68--78@
	unbalanced versions of test statistics for first-ordered
	serial correlation and random individual effects

.e SJ-8-1 @net: sj 8-1 st0140!st0140@
.c sj
.a K. C. Longest and S. Vaisey
.t ^fuzzy^: A prog. for performing qualitative comp. analyses (QCA)
.k stat-istics fuzzy prog-ramming prog-rams qualita-tive compar-isons compar-e
.k anal-ysis cmvom cnfgen coincid coverage fzplot
.k mavmb reduce setgen suffnec truthtab yavyb yvn yvo yvv yvy set-s
.k multiv-ariate data-sets boolean logit logic-al dicho-tomous
.k out-comes comb-inations cat-egorical
.k var-iables post-estimations est-imation est-imates command-s
.x
	(help @fuzzy@, @cmvom@, @cnfgen@, @coincid@, @coverage@, @fzplot@,
	@mavmb@, @reduce@, @setgen@, @suffnec@, @truthtab@, @yavyb@, @yvn@,
	@yvo@, @yvv@, @yvy@ if installed)
	Q1/08	@browser:http://www.stata-journal.com/article.html?article=st0140!SJ 8(1):79--104@
	provides qualitative comparative analysis (QCA) and
	fuzzy-set QCA

.e SJ-8-1 @net: sj 8-1 gr0031!gr0031@
.c sj
.a N. J. Cox
.t Speaking Stata: Spineplots and their kin
.k graph-s graph-ing graph-ics spineplot-s plot-s bar-s chart-s freq-uency
.k propor-tional propor-tions cat-egorical var-iables data-sets set-s
.k continu-ous anal-ysis horizont-ally stack-ed catplot tabplot percent-iles
.k colu-mns two-way way rbar conting-ency tabl-es region-s axis axes
.k cell-s vert-ically label-s cumul-ative mosaic
.o @spineplot@ if installed
.x
	Q1/08	@browser:http://www.stata-journal.com/article.html?article=gr0031!SJ 8(1):105--121@
	discusses spineplots (mosaic plots), a type of bar chart for
	showing frequencies, proportions, or percentages of cross-
	classified categorical variables

.e SJ-8-1 gn0038
.c sj
.a S. P. Jenkins
.t Review of ^Applied Health Economics^
.k book-s text-s review applied health econ-ometrics stat-istics anal-ysis
.k svy survey-s data-sets set-s surviv-al duration panel-s
.k jones rice bago duva balia
.x
	Q1/08	@browser:http://www.stata-journal.com/article.html?article=gn0038!SJ 8(1):122--128@				    (no commands)
	book review of ^Applied Health Economics^ by Jones,
	Rice, Bago d'Uva, and Balia (2007)

.e SJ-8-1 gn0039
.c sj
.a F. Kalter
.t Review of ^Event History Analysis with Stata^
.k book-s text-s review event histor-y anal-ysis stata transition data
.k model-s model-ing surviv-al tda blossfeld golsch rohwer
.x
	Q1/08	@browser:http://www.stata-journal.com/article.html?article=gn0039!SJ 8(1):129--133@				    (no commands)
	book review of ^Event History Analysis with Stata^ by
	Blossfeld, Golsch, and Rohwer (2007)

.e SJ-8-1 pr0037
.c sj
.a R. Gini
.t Stata tip 56: Writing parameterized text files
.k tip prog-ramming prog-rams text-s file-s manip-ulation writ-ten writ-e
.k param-eters param-etric param-eterization read-ing copy-ing global-ly
.k macro-s odbc sql code-s seq-uences
.x
	Q1/08	@browser:http://www.stata-journal.com/article.html?article=pr0037!SJ 8(1):134--136@				    (no commands)
	tip for writing parameterized text files

.e SJ-8-1 dm0035
.c sj
.a W. Gould
.t Stata tip 57: How to reinstall Stata
.k tip util-ity instal-ling instal-lation stata instal-ler
.k ado-files dir-ectories dir-ectory user-s writ-ten
.x
	Q1/08	@browser:http://www.stata-journal.com/article.html?article=dm0035!SJ 8(1):137--138@				    (no commands)
	tip on how to reinstall Stata including user-written
	commands

.e SJ-8-1 st0141
.c sj
.a B. P. Poi
.t Stata tip 58: ^nl^ is not just for nonlinear models
.k tip stat-istics nonlin-ear model-s nl linear transfo-rmations indep-endent
.k indep-endence var-iables marginal effect-s elas-ticities elas-ticity
.k reg-ressions est-imates est-imation constrain-ts
.x
	Q1/08	@browser:http://www.stata-journal.com/article.html?article=st0141!SJ 8(1):139--141@				    (no commands)
	tip showing examples where @nl@ is preferable to @regress@,
	even when the model is linear in the parameters

.e SJ-8-1 gr0032
.c sj
.a N. J. Cox
.t Stata tip 59: Plotting on any transformed scale
.k tip graph-s graph-ics graph-ing plot-s transfo-rmations scale-s axis axes
.k label-s propor-tional propor-tions logit line-s percent-iles macro-s
.k tick-s
.x
	Q1/08	@browser:http://www.stata-journal.com/article.html?article=gr0032!SJ 8(1):142--145@				    (no commands)
	tip on how to graph data on a transformed scale

.e SJ-8-1 @net:sj 8-1 st0126_1!st0126_1@
.c sj
.a J. Cui
.t QIC program and model selection in GEE analyses
.k stat-istics
.k general-ized est-imates est-imating eq-uations gee anal-ysis longi-tudinal
.k data quasi-likelihood like-lihood model-s selec-tion indep-endence
.k indep-endent criterion qic distrib-utions func-tions link corr-elations
.k akaike aic info-rmation reg-ressions param-eters structure bernoulli
.k norm-al poisson gamma neg-ative binom-ial inv-erse gauss-ian
.o @qic@ if installed
.x
	Q1/08	@browser:http://www.stata-journal.com/article.html?article=up0021!SJ 8(1):146@
	general negative binomial distribution now included with ^qic^

.e SJ-8-1 @net:sj 8-1 sxd1_3!sxd1_3@
.c sj
.a P. Ryan
.t Random allocation of treatments in blocks
.k stat-istics ralloc rct-s rand-omized control-led trial-s rand-omization
.k block-ed block-ing strat-ified factori-al design-s crossover switchback
.k alloc-ation treat-ments block-s
.o @ralloc@ if installed
.x
	Q1/08	@browser:http://www.stata-journal.com/article.html?article=up0021!SJ 8(1):146@
	update allows ^ralloc^ to support 10 treatments in a one-way
	design

.e SJ-7-4 @net: sj 7-4 st0067_3!st0067_3@
.c sj
.a P. Royston
.t Multiple imputation of missing values: Update of ^ice^
.k ice micombine mijoin misplit uvis cmdchk _mvis mvis
.k stat-istics data-sets set-s manage-ment miss-ing value-s
.k mult-iple multiv-ariate imput-e imput-ing imput-ation rubin-s rule-s
.k conf-idence interv-als est-imation est-imates model-s hot-deck deck
.k test-s test-ing surviv-al anal-ysis streg stcox rand-om reg-ressions
.k switch-ing pred-ictions match-ing mice box cox skew-ness skew-ed
.k ordinal restric-ted restric-tions ologit
.k censor-ed censor-ing obs-ervations right left mim reformat perfect svy
.k survey-s var-iables time event intreg outcome-s quantile-s q-qplots
.k plot-s kaplan-meier meier log-normal norm-al distrib-utions mfp
.k param-eters
.o @ice@, @ice_reformat@, @micombine@, @uvis@ if installed
.x
	Q4/07	@browser:http://www.stata-journal.com/article.html?article=st0067_3!SJ 7(4):445--464@
	update of ^ice^ allowing imputation of left-, right-, or
	interval-censored observations

.e SJ-7-4 @net:sj 7-4 st0030_3!st0030_3@
.c sj
.a C. F. Baum, M. E. Schaffer, and S. Stillman
.t Enhanced routines for IV/GMM estimation and testing
.k stat-istics est-imation est-imates gmm general-ized meth-ods mom-ents
.k iv instrum-ental var-iables test-s test-ing endog-enous endogeneity
.k hetero-skedasticity hetero-scedasticity overident-ification reg-ressions
.k restric-ted restric-tions robust clus-ters clus-tering group-s intra-groups
.k corr-elate corr-elations hansen sargan c j durbin wu hausman
.k ivendog ivhettest ivreg2 ivreg2_p ivreg_cue overid
.k routine autocor-relations std stand-ard err-ors ivactest ivreset ranktest
.k weak serial-ly hac liml limited info-rmation max-imum like-lihood
.k iv-regress identifier-s est-imators k class cov-ariances matr-ix ramsey
.k specifica-tion reset reg-ressors exog-enous infer-ence efficient
.k orthog-onalized cond-itional cond-itions inefficient asymp-totic variance-s
.k cov-ariances coef-ficients two-step step kern-el func-tions bartlett-s
.k newey-west west homosce-dasticity homoske-dasticity homog-eneity
.k distance-s rank-s canon-ical anderson-s rubin-s
.x
	(help @ivactest@, @ivendog@, @ivhettest@, @ivreg2@, @ivreset@,
	@overid@, @ranktest@ if installed)
	Q4/07	@browser:http://www.stata-journal.com/article.html?article=st0030_3!SJ 7(4):465--506@
	extension of IV and GMM estimation addressing hetero-
	skedasticity- and autocorrelation-consistent standard
	errors, weak instruments, LIML and k-class estimation,
	tests for endogeneity and Ramsey's regression
	specification-error test, and autocorrelation tests
	for IV estimates and panel-data IV estimates

.e SJ-7-4 st0136
.c sj
.a A. Nichols
.t Causal inference with observational data
.k stat-istics caus-al infer-ence obs-ervations data-sets set-s manage-ment
.k est-imates est-imation param-eters panel-s reg-ressions match-ing
.k instrum-ental var-iables discon-tinuities xt-reg psmatch2 nnmatch iv-reg2
.k iv-regress lpoly xt-overid propensity scor-es weak identifier-s
.k discon-tinuities local-ly poly-nomials treat-ments effect-s ordinary
.k method-s est-imators iv design-s model-s confound-ing ave-rages rubin-s
.k stable stabil-ity unit-s value-s assump-tions omit-ted bias-es bias-ed
.k selec-tion endog-enous endogeneity sensitiv-ity test-s test-ing system-s
.k equation-s group-s marginal linear fix-ed least sq-uares sq-uared ols
.k first diff-erences long clus-ters clus-tering clus-tered robust
.k rand-om indica-tor nearest neighbor-s bina-ry pscore sensatt mhbounds
.k decomp-osition error-s validity exog-enous two-stage stage 2 exclusion
.k restric-ted restric-tions reg-ressors specifica-tion reset overid
.k ivendog func-tional form-s std stand-ard err-ors wald dens-ity continu-ous
.k kdensity kern-el
.x
	Q4/07	@browser:http://www.stata-journal.com/article.html?article=st0136!SJ 7(4):507--541@				    (no commands)
	discusses problems with inferring causal relationships
	from nonexperimental data and describes four broad classes
	of methods designed to allow estimation of and inference
	about causal parameters

.e SJ-7-4 @net:sj 7-4 pr0034!pr0034@
.c sj
.a H. Stovring
.t A generic function evaluator implemented in Mata
.k prog-ramming prog-rams mata matr-ix lang-uage matr-ices
.k func-tions eval-uators num-erical num-bers composite distrib-utions
.k reverse-d nota-tion point-s pointer-s dens-ity polish rpn prob-abilities
.k prob-ability cumul-ative integration bina-ry oper-ators index stack-ed
.k ele-ments manip-ulation result-s rpnfcn exp-onential weibull arg-uments
.k dens-ity algor-ithms integr-ated integral-s eval-uation forw-ard
.k distrib-uted rand-om var-iables
.x
	(help @mf_rpnbinop@, @mf_rpndist@, @mf_rpnfcn@, @mf_rpnint@,
	@mf_rpnstackfcn@ if installed)
	Q4/07	@browser:http://www.stata-journal.com/article.html?article=pr0034!SJ 7(4):542--555@
	provides numerical evaluation in Mata of general,
	composite distributions specified using reverse Polish
	notation

.e SJ-7-4 pr0035
.c sj
.a W. Gould
.t Mata Matters: Structures
.k prog-ramming prog-rams mata matr-ix lang-uage feature-s new matr-ices
.k struct-ures subroutine routine compon-ents arg-uments var-iables
.k complex scal-ars vector-s optimiz-e func-tions point-s
.x
	Q4/07	@browser:http://www.stata-journal.com/article.html?article=pr0035!SJ 7(4):556--570@				    (no commands)
	focuses on @Mata@ structures as an advanced programming
	technique that can greatly simplify complicated code

.e SJ-7-4 dm0033
.c sj
.a N. J. Cox
.t Speaking Stata: Counting groups, especially panels
.k data-sets set-s manage-ment count-s count-ing group-s panel-s command-s
.k tab-ulations obs-ervations by: : egen identifier-s sort order-ed
.k var-iables inrange range cumul-ative sum-s
.x
	Q4/07	@browser:http://www.stata-journal.com/article.html?article=dm0033!SJ 7(4):571--581@				    (no commands)
	discusses how to count panels through reduction commands
	or through tabulation commands and how to overcome
	problems that do not yield easily to these approaches

.e SJ-7-4 dm0034
.c sj
.a N. J. Cox
.t Stata tip 52: Generating composite categorical variables
.k tip data-sets set-s manage-ment gen-erate composite cat-egorical var-iables
.k value-s str-ings num-erical label-s tostring identifier-s destring egen
.k group-s concat-enation
.x
	Q4/07	@browser:http://www.stata-journal.com/article.html?article=dm0034!SJ 7(4):582--583@				    (no commands)
	tip on how to generate categorical variables using
	@tostring@ and @egen, group()@

.e SJ-7-4 st0137
.c sj
.a M. L. Buis
.t Stata tip 53: Where did my p-values go?
.k tip stat-istics p-values value-s return-s result-s est-imation est-imates
.k t conf-idence interv-als param-eters upper lower bound-s model-s
.k report-ing z
.x
	Q4/07	@browser:http://www.stata-journal.com/article.html?article=st0137!SJ 7(4):584--586@				    (no commands)
	tip on calculating the t statistic, p-values, and
	confidence intervals using returned results

.e SJ-7-4 pr0036
.c sj
.a P. Van Kerm
.t Stata tip 54: Post your results
.k tip post-file post-close prog-ramming prog-rams postutil
.k monte carlo simul-ations exper-iments store result-s sav-ed sav-ing
.k file-s record-s
.x
	Q4/07	@browser:http://www.stata-journal.com/article.html?article=pr0036!SJ 7(4):587--589@				    (no commands)
	tip on using @post@ to accumulate results and save
	them for later use in an external file

.e SJ-7-4 gr0030
.c sj
.a N. J. Cox
.t Stata tip 55: Better axis labeling for time points/intervals
.k tip graph-s graph-ing graph-ics axis axes label-s plot-s point-s
.k interv-als time-series series data-sets set-s choice tick-s
.k date-s day calendar dow mdy month-ly year-ly
.x
	Q4/07	@browser:http://www.stata-journal.com/article.html?article=gr0030!SJ 7(4):590--592@				    (no commands)
	tip on labeling graphs for time points and time intervals

.e SJ-7-4 @net: sj 7-4 gr0012_1!gr0012_1@
.c sj
.a N. J. Cox
.t Software update for ^dpplot^
.k graph-s graph-ics graph-ing plot-s plot-ting kern-el dens-ity
.k distrib-utions prob-ability hist-ograms q-qplots quantile-s norm-al two-way
.k way est-imates rand-omized invnorm-al empir-ical diagnos-tics qnorm
.k probit normalden dpplot
.o @dpplot@ if installed
.x
	Q4/07	@browser:http://www.stata-journal.com/article.html?article=up0020!SJ 7(4):593@
	^addplot()^ option added

.e SJ-7-4 @net:sj 7-4 st0133_1!st0133_1@
.c sj
.a A. R. Hole
.t Software update for ^mixlogit^
.k stat-istics
.k fit-ting fit-ted mixed logit model-s max-imum like-lihood simul-ations
.k simulate simul-ated msl mixlogit mixlpred mixlcov est-imates est-imation
.k multin-omial prob-abilities cond-itional log-s norm-al log-normal group-s
.k pred-ictions pred-icted ele-ments coef-ficients cov-ariances matr-ix
.k ratio-s distrib-utions num-erical weight-s robust stand-ard err-ors std
.k clus-ters
.o @mixlogit@ if installed
.x
	Q4/07	@browser:http://www.stata-journal.com/article.html?article=up0020!SJ 7(4):593@
	estimation speed improved and new options added for
	specifying weights and for obtaining robust and cluster-
	robust standard errors

.e SJ-7-3 @net:sj 7-3 st0128!st0128@
.c sj
.a D. Hoechle
.t Robust std. err. for panel reg. with cross-sect. dependence
.k stat-istics
.k robust stand-ard err-ors std panel-s reg-ressions cross-section section-al
.k depend-ence xtscc est-imation est-imates est-imators pool-ing ordinary least
.k sq-uares sq-uared ols weight-ing weight-ed weight-s fix-ed effect-s
.k nonpar-ametric non param-etric cov-ariances covariate-s spatial data-sets
.k set-s rand-om matr-ix unbal-anced monte carlo simul-ations
.k hetero-scedasticity hetero-skedasticity corr-elations coef-ficients model-s
.k lag-s length selec-tion autocor-relations depend-ent specifica-tion
.k param-eters set-tings scenario hausman test-s test-ing linear
.k driscoll kraay
.o @xtscc@, @xtscc_postestimation@ if installed
.x
	Q3/07	@browser:http://www.stata-journal.com/article.html?article=st0128!SJ 7(3):281--312@
	estimates pooled ordinary least-squares/weighted least-squares
	regression and fixed-effects regression models with Driscoll
	and Kraay standard errors

.e SJ-7-3 @net:sj 7-3 st0129!st0129@
.c sj
.a X. Zheng and S. Rabe-Hesketh
.t Est. dichotomous & ordinal item response models with ^gllamm^
.k stat-istics
.k est-imates est-imation param-eters dicho-tomous ordinal item-s response-s
.k model-s order-ed gllamm gllapred theory meas-ures cat-egorical test-s
.k indirect latent scale-s logit var-iables general-ized linear mixed rasch
.k partial rat-ings reg-ressions adaptive quadra-ture raschtest bina-ry
.k logis-tic two 2 one 1 slope-s discrim-ination max-imum like-lihood ratio-s
.k scor-es post-erior mean-s empir-ical bayes-ian pred-ictions pred-icted
.o @gllamm@, @gllapred@ if installed
.x
	Q3/07	@browser:http://www.stata-journal.com/article.html?article=st0129!SJ 7(3):313--333@
	describes the one- and two-parameter logit models for
	dichotomous items, the partial-credit and rating scale
	models for ordinal items, and an extension of these models
	where the latent variable is regressed on explanatory
	variables

.e SJ-7-3 @net:sj 7-3 st0130!st0130@
.c sj
.a T. Nannicini
.t Simulation-based sensitivity anal. for matching estimators
.k stat-istics
.k simul-ations based sensitiv-ity anal-ysis match-ed match-ing est-imates
.k est-imation est-imators sensatt simul-ated robust treat-ments effect-s
.k dev-iations cond-itional indep-endence indep-endent assump-tions propensity
.k scor-es attnd attnw atts attr attk evaluation-s ave-rages psmatch2
.k nnmatch prob-abilities confound-ing param-eters std stand-ard err-ors
.k repli-cates replic-ations ext-ensions continu-ous outcome-s calibra-tion
.k bina-ry sav-ed result-s ichino mealli nannicini
.o @sensatt@ if installed
.x
	Q3/07	@browser:http://www.stata-journal.com/article.html?article=st0130!SJ 7(3):334--350@
	implements the sensitivity analysis for matching estimators
	proposed by Ichino, Mealli, and Nannicini

.e SJ-7-3 @net:sj 7-3 st0131!st0131@
.c sj
.a P. C. Lambert
.t Modeling of the cure fraction in survival studies
.k stat-istics
.k model-s model-ing cure frac-tions surviv-al study studies anal-ysis
.k propor-tional event curv-es strsmix strsnmix mix-tures pred-ictions
.k pred-icted relativ-e surviv-al split pop-ulations fit-ting stand-ard
.k ratio-s obs-ervations hazard lncure spurv cureregr specifica-tion
.k excess mortal-ity func-tions param-etric non-mixture distrib-utions
.k weibull log-normal norm-al gamma general-ized time link identity logis-tic
.k period-s vary-ing covariate-s est-imates est-imation est-imators max-imum
.k like-lihood ml-e post-estimations predictnl delta method-s exp-onential
.o @strsmix@, @strsnmix@ if installed
.x
	Q3/07	@browser:http://www.stata-journal.com/article.html?article=st0131!SJ 7(3):351--375@
	fits the mixture and nonmixture cure fraction models

.e SJ-7-3 @net:sj 7-3 st0132!st0132@
.c sj
.a P. Royston
.t Profile likelihood for estimation and confidence intervals
.k stat-istics
.k profile like-lihood est-imates est-imation conf-idence interv-als pllf
.k plot-s plot-ting max-imum param-eters reg-ressions model-s nonnorm-ality
.k nl non linear nonlin-ear norm-ality ml-e ratio-s log-s formula range
.k func-tions limit-s coef-ficients deviance covariate-s graph-s graph-ing
.k graph-ics asym-metry sym-metry effect-s size samp-ling samp-les
.o @pllf@ if installed
.x
	Q3/07	@browser:http://www.stata-journal.com/article.html?article=st0132!SJ 7(3):376--387@
	computes and plots the maximum likelihood estimate and
	profile likelihood-based confidence interval for one
	parameter in a wide variety of regression models

.e SJ-7-3 @net:sj 7-3 st0133!st0133@
.c sj
.a A. R. Hole
.t Fitting mixed logit models using max. simulated likelihood
.k stat-istics
.k fit-ting fit-ted mixed logit model-s max-imum like-lihood simul-ations
.k simulate simul-ated msl mixlogit mixlpred mixlcov est-imates est-imation
.k multin-omial prob-abilities cond-itional log-s norm-al log-normal group-s
.k pred-ictions pred-icted ele-ments coef-ficients cov-ariances matr-ix
.k ratio-s distrib-utions
.o @mixlogit@ if installed
.x
	Q3/07	@browser:http://www.stata-journal.com/article.html?article=st0133!SJ 7(3):388--401@
	fits mixed logit models by using maximum simulated likelihood

.e SJ-7-3 @net: sj 7-3 st0134!st0134@
.c sj
.a J. Kaiser
.t Fisher-Pitman perm. tests for paired rep. & indep. samples
.k stat-istics permtest1 permtest2 fisher-s exact non param-etric
.k pitman-s test-s test-ing signif-icance pair-s pair-ed repli-cates
.k p-values value-s samp-les samp-ling mean-s indep-endent permute
.k nonpar-ametric permu-tation algor-ithms monte carlo simul-ations
.o @permtest1@, @permtest2@ if installed
.x
	Q3/07	@browser:http://www.stata-journal.com/article.html?article=st0134!SJ 7(3):402--412@
	exact and Monte Carlo proposals to the nonparametric
	Fisher-Pitman tests for paired replicates and independent
	samples

.e SJ-7-3 @net: sj 7-3 gr0028!gr0028@
.c sj
.a N. J. Cox
.t Speaking Stata: Turning over a new leaf
.k graph-s graph-ing graph-ics stem-andleaf and-leaf and leaf
.k digit-s variant variance-s pref-erences compar-isons order-ed
.k value-s plot-s scat-terplots dot-s dotplot convert convers-ions
.k by clone clonevar label-s mark-s mark-ers axis axes
.k data-sets set-s anal-ysis final round-ed round-ing round-off
.k stemplot-s
.o @stemplot@ if installed
.x
	Q3/07	@browser:http://www.stata-journal.com/article.html?article=gr0028!SJ 7(3):413--433@
	discusses variants of stem-and-leaf plots using tools
	such as ^scatter, by()^ and a new command, ^stemplot^

.e SJ-7-3 pr0032
.c sj
.a M. L. Buis
.t Stata tip 48: Discrete uses for ^uniform()^
.k stat-istics
.k tip uniform-ly distrib-utions discrete rand-om samp-les samp-ling
.k draw-s ceil-ing func-tions
.x
	Q3/07	@browser:http://www.stata-journal.com/article.html?article=pr0032!SJ 7(3):434--435@				    (no commands)
	tip on using @uniform()@ to create random draws from a
	discrete distribution where each possible value has a
	known probability

.e SJ-7-3 gr0029
.c sj
.a S. Merryman
.t Stata tip 49: Range frame plots
.k tip plot-s scat-terplots graph-s graph-ing graph-ics axis axes
.k scale-s range region-s nofextend
.x
	Q3/07	@browser:http://www.stata-journal.com/article.html?article=gr0029!SJ 7(3):436--437@				    (no commands)
	tip on using undocumented option ^nofextend^ to force
	the axis lines to extend only over the range of data

.e SJ-7-3 st0135
.c sj
.a N. J. Cox
.t Stata tip 50: Efficient use of summarize
.k tip large data-sets set-s manage-ment summ-arize mean-s
.k mean-only sav-ed sav-ing result-s r-class
.x
	Q3/07	@browser:http://www.stata-journal.com/article.html?article=st0135!SJ 7(3):438--439@				    (no commands)
	tip on using the ^meanonly^ option of @summarize@ to more
	quickly determine the mean and other statistics of a
	large dataset

.e SJ-7-3 pr0033
.c sj
.a N. J. Cox
.t Stata tip 51: Events in intervals
.k tip prog-ramming prog-rams data-sets set-s manage-ment
.k panel-s longi-tudinal time interv-als sav-ed result-s
.k macro-s range for-values loop-s loop-ing
.x
	Q3/07	@browser:http://www.stata-journal.com/article.html?article=pr0033!SJ 7(3):440--443@				    (no commands)
	tip for counting or summarizing irregularly spaced
	events in intervals

.e SJ-7-3 @net: sj 7-3 st0015_4!st0015_4@
.c sj
.a T. J. Steichen and N. J. Cox
.t Software update for ^concord^
.k stat-istics concord-ance corr-elations coef-ficients lin graph-s graph-ics
.k limit-s agree-ment meas-urements compar-isons
.o @concord@ if installed
.x
	Q3/07	@browser:http://www.stata-journal.com/article.html?article=up0019!SJ 7(3):444@
	now compatible with Stata 10; help file updated

.e SJ-7-2 @net:sj 7-2 st0122!st0122@
.c sj
.a J. Shults, S. J. Ratcliffe, and M. Leonard
.t Improved GEE analysis via ^xtqls^ for quasi-least squares
.k stat-istics
.k general-ized est-imation est-imates equation-s anal-ysis xtqls quasi least
.k sq-uares corr-elations param-eters gee cross section-al longi-tudinal qls
.k xt-gee data-sets set-s clus-tered clus-ters clus-tering outcome-s
.k var-iables covariate-s first order-ed autoregr-essive autoregr-essions
.k structure linear model-s reg-ressions exch-angeable mov-ing ave-rages
.k identity unstruc-tured robust sandw-ich matr-ix limit-s limit-ed
.k unbal-anced bal-anced two-stage stage 2 err-ors sum-s sq-uared square-s
.k alpha beta hat expand canon-ical link func-tions logis-tic algor-ithms
.k sav-ed result-s markov space meas-ures meas-urements equi-correlated
.o @xtqls@ if installed
.x
	Q2/07	@browser:http://www.stata-journal.com/article.html?article=st0122!SJ 7(2):147--166@
	uses QLS as an alternative for estimating correlation
	parameters within a GEE model

.e SJ-7-2 @net:sj 7-2 st0123!st0123@
.c sj
.a R. Chiburis and M. Lokshin
.t ML and two-step estimation of ordered-probit selection model
.k stat-istics
.k max-imum like-lihood two-step step est-imation est-imates order-ed probit
.k selec-tion model-s reg-ressions oheckman monte carlo simul-ations bias
.k fiml info-rmation algor-ithms linear specifica-tion rule-s log-s
.k identify-ing problem-s d2 method-s ml-e pred-icted pred-ictions sav-ed
.k result-s examp-les data-sets gen-erate process-es baseline corr-elate
.k corr-elations err-ors mult-iple equation-s nonnorm-ality shoc-ks
.k exclusion restric-ted restric-tions
.o @oheckman@ if installed
.x
	Q2/07	@browser:http://www.stata-journal.com/article.html?article=st0123!SJ 7(2):167--182@
	two-step and full-information maximum likelihood (FIML)
	estimation of a regression model with an ordered-probit
	selection rule

.e SJ-7-2 @net:sj 7-2 st0124!st0124@
.c sj
.a Z. Wang
.t Commands for assessing confounding effects in epi. studies
.k stat-istics
.k post-estimations est-imation est-imates command-s confound-ing effect-s
.k epi-demiology epi-demiological studies study confall plot-s akaike-s
.k info-rmation criterion aic bayes-ian bic chest stepwise confgr method-s
.k change bias strat-ified strat-ification mult-iple reg-ressions display-ing
.k calcul-ate calcul-ations
.o @chest@, @confall@, @confgr@ if installed
.x
	Q2/07	@browser:http://www.stata-journal.com/article.html?article=st0124!SJ 7(2):183--196@
	two postestimation commands for assessing confounding
	effects in epidemiological studies

.e SJ-7-2 @net:sj 7-2 st0125!st0125@
.c sj
.a E. F. Blackburne, III and M. W. Frank
.t Estimation of nonstationary heterogeneous panels
.k stat-istics
.k est-imates est-imation est-imators nonstatio-nary heterog-eneity panel-s
.k xtpmg fix-ed effect-s mean-s group-s pool dynamic coint-egrating
.k coint-egration var-iables ave-rages max-imum like-lihood ml-e large
.k coef-ficients cross section-al obs-ervations num-bers time-series series
.o @xtpmg@ if installed
.x
	Q2/07	@browser:http://www.stata-journal.com/article.html?article=st0125!SJ 7(2):197--208@
	estimates nonstationary heterogeneous panels in which the
	number of groups and number of time-series observations
	are both large

.e SJ-7-2 @net:sj 7-2 st0126!st0126@
.c sj
.a J. Cui
.t QIC program and model selection in GEE analyses
.k stat-istics
.k general-ized est-imates est-imating eq-uations gee anal-ysis longi-tudinal
.k data quasi-likelihood like-lihood model-s selec-tion indep-endence
.k indep-endent criterion qic distrib-utions func-tions link corr-elations
.k akaike aic info-rmation reg-ressions param-eters structure bernoulli
.k norm-al poisson gamma neg-ative binom-ial inv-erse gauss-ian
.o @qic@ if installed
.x
	Q2/07	@browser:http://www.stata-journal.com/article.html?article=st0126!SJ 7(2):209--220@
	provides the quasilikelihood under the independence
	model criterion (QIC) method for GEE model selection

.e SJ-7-2 st0127
.c sj
.a M. L. Buis
.t ^predict^ and ^adjust^ with logistic regression
.k stat-istics
.k pred-ictions pred-icted adjust-ed logis-tic reg-ressions ave-rages value-s
.k est-imates est-imation command-s prob-abilities diff-erences
.k nonlin-ear transfo-rmations linear pred-ictor mean-s
.x
	Q2/07	@browser:http://www.stata-journal.com/article.html?article=st0127!SJ 7(2):221--226@				    (no commands)
	discusses subtle differences in interpretation of average
	predicted values computed by @adjust@ and @predict@ after
	logistic regression

.e SJ-7-2 @net: sj 7-2 st0085_1!st0085_1@
.c sj
.a B. Jann
.t Making regression tables simplified
.k est-imation est-imates reg-ressions spread-sheets mfx marginal effect-s
.k tabl-es latex format-s format-ting tab-ulate tab-ulations html
.k stat-istics publication store scal-ars rank-s p r-2 conf-idence interv-als
.k schwartz schwarz akaike-s aic bic coef-ficients summ-ary t z label-s
.k mult-iple eq-uations model-s ereturn descrip-tive
.k estadd estout estoutdef estadd_beta estadd_mean estadd_sd
.k estadd_sd eststo esttab result-s csv comma-s separ-ated word ms-word
.k excel name-s prefix command-s by change content-s titl-es bayes-ian
.k info-rmation criterion num-erical out-putting smcl fix-ed fmt
.o @estadd@, @estout@, @_eststo@, @eststo@, @esttab@ if installed
.x
	Q2/07	@browser:http://www.stata-journal.com/article.html?article=st0085_1!SJ 7(2):227--244@
	introduces the ^eststo^ and ^esttab^ commands (stemming from
	^estout^) that simplify making regression tables from stored
	estimates

.e SJ-7-2 gn0037
.c sj
.a W. D. Dupont
.t Review of ^A Handbook of Statistical Analyses Using Stata^
.k stat-istics rabe hesketh everitt gllamm stata text-s book-s
.k book-store intro-duction teach-ing review
.x
	Q2/07	@browser:http://www.stata-journal.com/article.html?article=gn0037!SJ 7(2):245--248@				    (no commands)
	book review of ^A Handbook of Statistical Analyses Using^
	^Stata, 4th ed^ by Rabe-Hesketh and Everitt, 2007

.e SJ-7-2 dm0029
.c sj
.a N. J. Cox
.t Speaking Stata: Identifying spells
.k stat-istics identify-ing spell-s seq-uences obs-ervations tag by: : prefix
.k by sort order-ed run-s data-sets set-s manage-ment time-series series
.k cat-egorical meas-urements meas-ures panel-s gap-s homog-eneity
.k longi-tudinal identifier-s indica-tor var-iables structure propert-ies
.k length num-bers last space if in cond-itional miss-ing value-s
.k censor-ed censor-ing
.x
	Q2/07	@browser:http://www.stata-journal.com/article.html?article=dm0029!SJ 7(2):249--265@				    (no commands)
	shows how to handle spells with complete control over
	spell specification

.e SJ-7-2 dm0030
.c sj
.a B. Jann
.t Stata tip 44: Get a handle on your sample
.k tip data-sets set-s manage-ment handl-ing samp-les samp-ling stat-istics
.k anal-ysis obs-ervations if in condition miss-ing value-s pred-ictors
.k pred-ictions covariate-s bina-ry indica-tor dum-my dum-mies var-iables
.k mark-sample markout
.x
	Q2/07	@browser:http://www.stata-journal.com/article.html?article=dm0030!SJ 7(2):266--267@				    (no commands)
	tip on how to keep track of the observations that make
	up your estimation sample

.e SJ-7-2 dm0031
.c sj
.a C. F. Baum and N. J. Cox
.t Stata tip 45: Getting those data into shape
.k tip data-sets set-s manage-ment reshape structure anal-ysis anal-ysis
.k modify wide long transfo-rmations exch-angeable csv comma-s separ-ated
.k value-s
.x
	Q2/07	@browser:http://www.stata-journal.com/article.html?article=dm0031!SJ 7(2):268--271@				    (no commands)
	tip on applications of @reshape@ and solving data
	management problems

.e SJ-7-2 dm0032
.c sj
.a R. Williams
.t Stata tip 46: Step we gaily, on we go
.k tip stat-istics nestreg-: : command-s prefix stepwise
.k est-imates est-imation seq-uences nest-ed nest-ing model-s var-iables
.k order-ed wald stat-istics like-lihood ratio-s chi-squared sq-uared chi-2 2
.k bayes-ian info-rmation criterion bic akaike-s aic
.x
	Q2/07	@browser:http://www.stata-journal.com/article.html?article=dm0032!SJ 7(2):272--274@				    (no commands)
	tip on @nestreg@ and @stepwise@ prefix commands

.e SJ-7-2 gr0027
.c sj
.a N. J. Cox
.t Stata tip 47: Quantile-quantile plots without programming
.k tip graph-s graph-ing graph-ics quantile-s plot-s prog-ramming prog-rams
.k stat-istics distrib-utions fit-ting fit-s fit-ted obs-erved norm-al
.k qnorm chi-squared sq-uared chi-2 2 qchi egen func-tions prob-ability
.k gumbel param-eters
.x
	Q2/07	@browser:http://www.stata-journal.com/article.html?article=gr0027!SJ 7(2):275--279@				    (no commands)
	tip on producing various quantile-quantile (Q-Q) plots

.e SJ-7-2 @net: sj 7-2 gr0001_3!gr0001_3@
.c sj
.a P. Van Kerm and S. P. Jenkins
.t Software update for ^glcurve^
.k stat-istics lorenz curv-es graph-s graph-ing graph-ics distrib-utions
.k income glc general-ized inequal-ity meas-ures
.k disper-sion segre-gation glcurve-7
.k concentra-tion tip sort order-ed
.o @glcurve@ if installed
.x
	Q2/07	@browser:http://www.stata-journal.com/article.html?article=up0018!SJ 7(2):280@
	updated to have a stable sort in increasing order of the
	outcome variable within ties of the ordering variable

.e SJ-7-2 @net: sj 7-2 st0097_1!st0097_1@
.c sj
.a R. Williams
.t Software update for ^gologit2^
.k stat-istics gologit gologit2 gologit2_ll gologit2_p pred-ictions
.k reg-ressions general-ized logis-tic ordinal propor-tional odd-s partial
.k order-ed logit model-s paral-lel line-s lin-ear constrain-ts svy-: survey-s
.k data brant test-s test-ing bina-ry wald step-wise backward selec-tion gamma
.k param-eters param-etric param-eterization est-imates est-imation
.k link func-tions prefix command-s
.o @gologit2@ if installed
.x
	Q2/07	@browser:http://www.stata-journal.com/article.html?article=up0018!SJ 7(2):280@
	now supports prefix commands and allows different link
	functions

.e SJ-7-1 st0118
.c sj
.a F. Kreuter and R. Valliant
.t A survey on survey stat.: What is and can be done in Stata
.k stat-istics
.k clus-ters clus-tering clus-tered samp-les samp-ling survey-s svy
.k complex design-s strat-ified anal-ysis variance-s est-imates est-imations
.k weight-s anal-yze data complex bias-ed common method-s
.k taylor repli-cates replic-ations feature-s strat-ification
.k prob-ability strata primary unit-s psu stand-ard err-ors meff deff
.k deft delta stratum svyset svydes-cribe subset-s group-s subpop-ulations
.k pop-ulations defect nhanes nhis pisa
.x
	Q1/07	@browser:http://www.stata-journal.com/article.html?article=st0118!SJ 7(1):1--21@				    (no commands)
	discusses survey issues in analyzing complex survey
	data and describes some of Stata's capabilities for
	such analyses

.e SJ-7-1 @net:sj 7-1 st0119!st0119@
.c sj
.a J. Hardouin
.t Rasch analysis: Estimation and tests with ^raschtest^
.k stat-istics
.k raschtest-v7 rasch model-s model-ing general-ized est-imates est-imation
.k equation-s cond-itional max-imum like-lihoodratio method-s marginal andersen
.k z test-s test-ing fit-ted fit-s fit-ting item-s response-s theory irt u
.k split-ting character-istics curv-es bina-ry ordinal var-iables dicho-tomous
.k local-ly indep-endence indep-endent fix-ed effect-s param-eters
.k func-tions rand-om ratio-s first order-ed infit outfit graph-s graph-ing
.k graph-ics clogit xtlogit geekel2d gllamm gllapred gammasym gausshermite
.k genscore ghquadm elapse gee van den wollenberg vandenwoll-enberg q1 r1c r1m
.x
	(help @gammasym@, @gausshermite@, @geekel2d@, @raschtest@,
	@raschtestv7@ if installed)
	Q1/07	@browser:http://www.stata-journal.com/article.html?article=st0119!SJ 7(1):22--44@
	command for estimating the Rasch model, the best known
	item response theory model for binary responses

.e SJ-7-1 @net:sj 7-1 st0120!st0120@
.c sj
.a P. Royston and W. Sauerbrei
.t Multivar. modeling with cubic reg. splines: A prin. approach
.k stat-istics
.k mvrs uvrs splinegen multivariable anal-ysis continu-ous pred-ictor
.k reg-ressions spline-s model-s model-ing goodness fit scale-s choice
.k cub-ic mfp frac-tional poly-nomials func-tions var-iables smooth-ing
.k smooth-ers univar-iate out-comes default robust transfo-rmations value-s
.k algor-ithms selec-tion est-imation
.o @mvrs@, @uvrs@, @splinegen@ if installed
.x
	Q1/07	@browser:http://www.stata-journal.com/article.html?article=st0120!SJ 7(1):45--70@
	discusses how to limit instability and provide sensible
	regression models when using spline functions in a
	multivariable setting

.e SJ-7-1 @net:sj 7-1 st0121!st0121@
.c sj
.a S. O. Becker and M. Caliendo
.t Sensitivity analysis for average treatment effects
.k stat-istics
.k mhbounds match-ed match-ing sensitiv-ity anal-ysis ave-rages treat-ments
.k effect-s est-imation est-imates unobs-erved heterog-eneity bound-ed bound-s
.k var-iables model-s model-ing bina-ry outcome-s mantel-haenszel haenszel
.k test-s test-ing rosenbaum
.o @mhbounds@ if installed
.x
	Q1/07	@browser:http://www.stata-journal.com/article.html?article=st0121!SJ 7(1):71--83@
	uses Rosenbaum's bounding approach to evaluate potential
	bias problems in the use of matching in estimating average
	treatment effects

.e SJ-7-1 pr0027
.c sj
.a P. Vittorini, S. Necozione, F. di Orio
.t Stata and the WeeW information system
.k prog-ramming prog-rams
.k weew info-rmation system web-sites site-s based www internet epi-demiology
.k epi-demiological graph-s graph-ing graph-ics interface
.k anal-ysis data-sets set-s manage-ment workflow stat-istics database
.k stata csv comma-s separ-ated
.x
	Q1/07	@browser:http://www.stata-journal.com/article.html?article=pr0027!SJ 7(1):84--97@				    (no commands)
	introduces WeeW, a workflow-enabled epidemiological WIS
	system that aids in workflow management, collection, and
	processing received data to produce technical reports

.e SJ-7-1 @net:sj 7-1 dm0027!dm0027@
.c sj
.a J. Eng
.t File filtering: Handling complex data formats and log files
.k data-sets set-s manage-ment
.k file-s filter complex format-s format-ting format-ted log-s text-s
.k convert convers-ions null-filter match-filter hyperlog import-ing expor-t
.k html hyperlink index web-sites site-s www temp-orary name-s loop-ing loop-s
.k compound double-s quot-ation mark-s quot-es str-ings length limit-s
.k tab charac-ters gen-erate
.o @hyperlog@ if installed
.x
	Q1/07	@browser:http://www.stata-journal.com/article.html?article=dm0027!SJ 7(1):98--105@
	reviews key programming points for successful implementation
	of file filters

.e SJ-7-1 pr0028
.c sj
.a W. Gould
.t Mata Matters: Subscripting
.k mata prog-ramming prog-rams
.k subsc-ripts subsc-ripting matr-ix list-s range samp-les samp-ling
.k permu-tation matr-ices vec-tors simple comma-s oper-ators replacem-ent
.x
	Q1/07	@browser:http://www.stata-journal.com/article.html?article=pr0028!SJ 7(1):106--116@				    (no commands)
	focuses on the three subscripting modes of Stata

.e SJ-7-1 pr0029
.c sj
.a N. J. Cox
.t Speaking Stata: Making it ^count^
.k stat-istics count-s count-ing num-bers obs-ervations data-sets set-s
.k manage-ment drop-ped drop-ping var-iables find match-es match-ed match-ing
.k egen loop-ing loop-s by if in expr-essions
.x
	Q1/07	@browser:http://www.stata-journal.com/article.html?article=pr0029!SJ 7(1):117--130@				    (no commands)
	discusses ^count^ used with a loop over observations
	or variables

.e SJ-7-1 gn0036
.c sj
.a A. Nichols
.t Review of ^Intro. to Modern Econometrics Using Stata^ by Baum
.k book-s text-s review intro-duction baum
.k stat-istics teach-ing book-store learn-ing stata econ-ometrics
.x
	Q1/07	@browser:http://www.stata-journal.com/article.html?article=gn0036!SJ 7(1):131--136@				    (no commands)
	book review of ^An Introduction to Modern Econometrics^
	^Using Stata^ by Baum (2006)

.e SJ-7-1 dm0028
.c sj
.a C. F. Baum
.t Stata tip 40: Taking care of business
.k tip day daily time-series series date-s var-iables
.k sequen-tial data-sets set-s manage-ment
.x
	Q1/07	@browser:http://www.stata-journal.com/article.html?article=dm0028!SJ 7(1):137--139@				    (no commands)
	tip for dealing with time-series date schemes and how to
	handle gaps

.e SJ-7-1 pr0030
.c sj
.a D. A. Harrison
.t Stata tip 41: Monitoring loop iterations
.k tip loop-ing loop-s iter-ations dot-s prog-ramming prog-rams
.x
	Q1/07	@browser:http://www.stata-journal.com/article.html?article=pr0030!SJ 7(1):140@					    (no commands)
	tip for monitoring loops

.e SJ-7-1 gr0026
.c sj
.a J. Cui
.t Stata tip 42: The overlay problem: Offset for clarity
.k tip graph-s graph-ing graph-ics axis axes discrete continu-ous
.k scale-s overlap-ping offset
.x
	Q1/07	@browser:http://www.stata-journal.com/article.html?article=gr0026!SJ 7(1):141--142@				    (no commands)
	tip for graphing several quantities on a continuous axis

.e SJ-7-1 pr0031
.c sj
.a N. J. Cox
.t Stata tip 43: Remainders, selections, sequences, extractions
.k tip remain-der selec-tion seq-uences extrac-tion mod-ulus func-tions
.k loop-ing loop-s gen-erate prog-ramming prog-rams
.x
	Q1/07	@browser:http://www.stata-journal.com/article.html?article=pr0031!SJ 7(1):143--145@				    (no commands)
	tip for uses of the modulus
