{smcl}
{* *! version 1.2.18  03jun2011}{...}
{viewerdialog oprobit "dialog oprobit"}{...}
{viewerdialog "svy: oprobit" "dialog oprobit, message(-svy-) name(svy_oprobit)"}{...}
{vieweralsosee "[R] oprobit" "mansection R oprobit"}{...}
{vieweralsosee "" "--"}{...}
{vieweralsosee "[R] oprobit postestimation" "help oprobit postestimation"}{...}
{vieweralsosee "" "--"}{...}
{vieweralsosee "[MI] estimation" "help mi estimation"}{...}
{vieweralsosee "[R] logistic" "help logistic"}{...}
{vieweralsosee "[R] mlogit" "help mlogit"}{...}
{vieweralsosee "[R] mprobit" "help mprobit"}{...}
{vieweralsosee "[R] ologit" "help ologit"}{...}
{vieweralsosee "[R] probit" "help probit"}{...}
{vieweralsosee "[SVY] svy estimation" "help svy_estimation"}{...}
{viewerjumpto "Syntax" "oprobit##syntax"}{...}
{viewerjumpto "Description" "oprobit##description"}{...}
{viewerjumpto "Options" "oprobit##options"}{...}
{viewerjumpto "Examples" "oprobit##examples"}{...}
{viewerjumpto "Saved results" "oprobit##saved_results"}{...}
{title:Title}

{p2colset 5 20 22 2}{...}
{p2col :{manlink R oprobit} {hline 2}}Ordered probit regression{p_end}
{p2colreset}{...}


{marker syntax}{...}
{title:Syntax}

{p 8 16 2}
{cmdab:oprob:it}
{depvar}
[{indepvars}]
{ifin}
{weight}
{bind:[{cmd:,} {it:options}]}

{synoptset 28 tabbed}{...}
{synopthdr}
{synoptline}
{syntab :Model}
{synopt :{opth off:set(varname)}}include {it:varname} in model with coefficient constrained to 1{p_end}
{synopt :{cmdab:const:raints(}{it:{help estimation options##constraints():constraints}}{cmd:)}}apply specified linear constraints{p_end}
{synopt:{opt col:linear}}keep collinear variables{p_end}

{syntab :SE/Robust}
{synopt :{opth vce(vcetype)}}{it:vcetype} may be {opt oim},
   {opt r:obust}, {opt cl:uster} {it:clustvar}, {opt boot:strap}, or
   {opt jack:knife}{p_end}

{syntab :Reporting}
{synopt :{opt l:evel(#)}}set confidence level; default is {cmd:level(95)}{p_end}
{synopt :{opt nocnsr:eport}}do not display constraints{p_end}
{synopt :{it:{help oprobit##display_options:display_options}}}control
INCLUDE help shortdes-displayoptall

{syntab :Maximization}
{synopt :{it:{help oprobit##maximize_options:maximize_options}}}control the maximization process; seldom used{p_end}

INCLUDE help shortdes-coeflegend
{synoptline}
{p2colreset}{...}
INCLUDE help fvvarlist
{p 4 6 2}{it:depvar} and {it:indepvars} may contain time-series operators; see {help tsvarlist}.{p_end}
{p 4 6 2}
{opt bootstrap}, {opt by}, {opt fracpoly}, {opt jackknife}, {opt mfp},
{opt mi estimate}, {opt nestreg}, {opt rolling}, {opt statsby},
{opt stepwise}, and {opt svy} are allowed; see {help prefix}.{p_end}
INCLUDE help vce_mi
{p 4 6 2}Weights are not allowed with the {helpb bootstrap} prefix.{p_end}
{p 4 6 2}
{opt vce()} and weights are not allowed with the {helpb svy} prefix.
{p_end}
{p 4 6 2}
{opt fweight}s, {opt iweight}s, and {opt pweight}s are allowed;
see {help weight}.{p_end}
{p 4 6 2}
{opt coeflegend} does not appear in the dialog box.{p_end}
{p 4 6 2}
See {manhelp oprobit_postestimation R:oprobit postestimation} for features
available after estimation.  {p_end}


{title:Menu}

{phang}
{bf:Statistics > Ordinal outcomes > Ordered probit regression}


{marker description}{...}
{title:Description}

{pstd}
{opt oprobit} fits ordered probit models of ordinal variable
{depvar} on the independent variables {indepvars}.
The actual values taken on by the
dependent variable are irrelevant, except that larger values are assumed to
correspond to "higher" outcomes.

{pstd}
See {help logistic estimation commands} for a list of related estimation
commands.


{marker options}{...}
{title:Options}

{dlgtab:Model}

{phang}
{opth offset(varname)},
{opt constraints(constraints)}, {opt collinear}; see
{helpb estimation options:[R] estimation options}.

{dlgtab:SE/Robust}

INCLUDE help vce_asymptall

{dlgtab:Reporting}

{phang}
{opt level(#)}; see
{helpb estimation options##level():[R] estimation options}.

{phang}
{opt nocnsreport}; see
     {helpb estimation options##nocnsreport:[R] estimation options}.

{marker display_options}{...}
{phang}
{it:display_options}:
{opt noomit:ted},
{opt vsquish},
{opt noempty:cells},
{opt base:levels},
{opt allbase:levels},
{opth cformat(%fmt)},
{opt pformat(%fmt)},
{opt sformat(%fmt)}, and
{opt nolstretch};
    see {helpb estimation options##display_options:[R] estimation options}.

{marker maximize_options}{...}
{dlgtab:Maximization}

{phang}
{it:maximize_options}:
{opt dif:ficult},
{opth tech:nique(maximize##algorithm_spec:algorithm_spec)},
{opt iter:ate(#)}, [{cmd:{ul:no}}]{opt lo:g}, {opt tr:ace}, 
{opt grad:ient}, {opt showstep},
{opt hess:ian},
{opt showtol:erance},
{opt tol:erance(#)},
{opt ltol:erance(#)}, 
{opt nrtol:erance(#)},
{opt nonrtol:erance}, and
{opt from(init_specs)}; see {manhelp maximize R}.  These options are seldom
used.

{pstd}
The following option is available with {opt oprobit} but is not shown in the
dialog box:

{phang}
{opt coeflegend}; see
     {helpb estimation options##coeflegend:[R] estimation options}.


{marker examples}{...}
{title:Examples}

    {hline}
{pstd}Setup{p_end}
{phang2}{cmd:. webuse fullauto}{p_end}

{pstd}Ordered probit regression{p_end}
{phang2}{cmd:. oprobit rep77 foreign length mpg}{p_end}

    {hline}
{pstd}Setup{p_end}
{phang2}{cmd:. webuse nhanes2f}{p_end}
{phang2}{cmd:. svyset psuid [pw=finalwgt], strata(stratid)}

{pstd}Ordered probit regression using survey data{p_end}
{phang2}{cmd:. svy: oprobit health female black age c.age#c.age}{p_end}
    {hline}


{marker saved_results}{...}
{title:Saved results}

{pstd}
{cmd:oprobit} saves the following in {cmd:e()}:

{synoptset 15 tabbed}{...}
{p2col 5 15 19 2: Scalars}{p_end}
{synopt:{cmd:e(N)}}number of observations{p_end}
{synopt:{cmd:e(N_cd)}}number of completely determined observations{p_end}
{synopt:{cmd:e(k_cat)}}number of categories{p_end}
{synopt:{cmd:e(k)}}number of parameters{p_end}
{synopt:{cmd:e(k_aux)}}number of auxiliary parameters{p_end}
{synopt:{cmd:e(k_eq)}}number of equations in {cmd:e(b)}{p_end}
{synopt:{cmd:e(k_eq_model)}}number of equations in overall model test{p_end}
{synopt:{cmd:e(k_dv)}}number of dependent variables{p_end}
{synopt:{cmd:e(df_m)}}model degrees of freedom{p_end}
{synopt:{cmd:e(r2_p)}}pseudo-R-squared{p_end}
{synopt:{cmd:e(ll)}}log likelihood{p_end}
{synopt:{cmd:e(ll_0)}}log likelihood, constant-only model{p_end}
{synopt:{cmd:e(N_clust)}}number of clusters{p_end}
{synopt:{cmd:e(chi2)}}chi-squared{p_end}
{synopt:{cmd:e(p)}}significance{p_end}
{synopt:{cmd:e(rank)}}rank of {cmd:e(V)}{p_end}
{synopt:{cmd:e(ic)}}number of iterations{p_end}
{synopt:{cmd:e(rc)}}return code{p_end}
{synopt:{cmd:e(converged)}}{cmd:1} if converged, {cmd:0} otherwise{p_end}

{synoptset 20 tabbed}{...}
{p2col 5 20 24 2: Macros}{p_end}
{synopt:{cmd:e(cmd)}}{cmd:oprobit}{p_end}
{synopt:{cmd:e(cmdline)}}command as typed{p_end}
{synopt:{cmd:e(depvar)}}name of dependent variable{p_end}
{synopt:{cmd:e(wtype)}}weight type{p_end}
{synopt:{cmd:e(wexp)}}weight expression{p_end}
{synopt:{cmd:e(title)}}title in estimation output{p_end}
{synopt:{cmd:e(clustvar)}}name of cluster variable{p_end}
{synopt:{cmd:e(offset)}}linear offset variable{p_end}
{synopt:{cmd:e(chi2type)}}{cmd:Wald} or {cmd:LR}; type of model chi-squared test{p_end}
{synopt:{cmd:e(vce)}}{it:vcetype} specified in {cmd:vce()}{p_end}
{synopt:{cmd:e(vcetype)}}title used to label Std. Err.{p_end}
{synopt:{cmd:e(opt)}}type of optimization{p_end}
{synopt:{cmd:e(which)}}{cmd:max} or {cmd:min}; whether optimizer is to perform
                     maximization or minimization{p_end}
{synopt:{cmd:e(ml_method)}}type of {cmd:ml} method{p_end}
{synopt:{cmd:e(user)}}name of likelihood-evaluator program{p_end}
{synopt:{cmd:e(technique)}}maximization technique{p_end}
{synopt:{cmd:e(properties)}}{cmd:b V}{p_end}
{synopt:{cmd:e(predict)}}program used to implement {cmd:predict}{p_end}
{synopt:{cmd:e(asbalanced)}}factor variables {cmd:fvset} as {cmd:asbalanced}{p_end}
{synopt:{cmd:e(asobserved)}}factor variables {cmd:fvset} as {cmd:asobserved}{p_end}

{synoptset 20 tabbed}{...}
{p2col 5 20 24 2: Matrices}{p_end}
{synopt:{cmd:e(b)}}coefficient vector{p_end}
{synopt:{cmd:e(Cns)}}constraints matrix{p_end}
{synopt:{cmd:e(ilog)}}iteration log (up to 20 iterations){p_end}
{synopt:{cmd:e(gradient)}}gradient vector{p_end}
{synopt:{cmd:e(cat)}}category values{p_end}
{synopt:{cmd:e(V)}}variance-covariance matrix of the estimators{p_end}
{synopt:{cmd:e(V_modelbased)}}model-based variance{p_end}

{synoptset 20 tabbed}{...}
{p2col 5 20 24 2: Functions}{p_end}
{synopt:{cmd:e(sample)}}marks estimation sample{p_end}
{p2colreset}{...}
