truncreg.hlp

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{smcl}
{* 18mar2005}{...}
{cmd:help truncreg}{...}
{right:dialog:  {bf:{dialog truncreg}}{space 15}}
{right:also see:  {help truncreg postestimation}}
{hline}

{title:Title}

{p2colset 5 21 23 2}{...}
{p2col:{hi:[R] truncreg} {hline 2}}Truncated regression{p_end}
{p2colreset}{...}


{title:Syntax}

{p 8 17 2}
{cmd:truncreg}
{depvar}
[{indepvars}]
{ifin}
{weight}
[{cmd:,} {it:options}]

{synoptset 28 tabbed}{...}
{synopthdr}
{synoptline}
{syntab:Model}
{synopt:{opt nocon:stant}}suppress constant term
{p_end}
{synopt:{cmd:ll(}{varname}|{it:#}{cmd:)}}lower limit for left truncation
{p_end}
{synopt:{cmd:ul(}{varname}|{it:#}{cmd:)}}upper limit for right truncation
{p_end}

{syntab:Model 2}
{synopt:{opth off:set(varname)}}include {it:varname} in model with
coefficient constrained to 1
{p_end}
{synopt:{opt m:arginal}}estimate the marginal effects
{p_end}
{synopt:{opt at(matname)}}point at which to estimate marginal effect
{p_end}
{synopt:{cmdab:const:raints(}{it:{help estimation options##constraints():constraints}}{cmd:)}}apply specified linear constraints
{p_end}

{syntab:SE/Robust}
{synopt:{opth vce(vcetype)}}{it:vcetype} may be {opt oim}, {opt r:obust}, {opt opg}, {opt boot:strap}, or {opt jack:knife}
{p_end}
{synopt:{opt r:obust}}synonym for {cmd:vce(robust)}
{p_end}
{synopt:{opth cl:uster(varname)}}adjust standard errors for intragroup
correlation
{p_end}

{syntab:Reporting}
{synopt:{opt l:evel(#)}}set confidence level; default is {cmd:level(95)}
{p_end}
{synopt:{opt noskip}}perform likelihood-ratio test
{p_end}

{syntab:Max options}
{synopt:{it:{help truncreg##maximize_options:maximize_options}}}control
maximization process; seldom used
{p_end}
{synoptline}
{p2colreset}{...}
{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 jackknife}, {opt rolling}, {opt statsby}, and
{opt xi} are allowed; see {help prefix}.
	{p_end}
{p 4 6 2}
{opt aweight}s, {opt fweight}s, and {opt pweight}s are allowed;
see {help weight}.
	{p_end}
{p 4 6 2}
See {help truncreg postestimation} for features available after estimation.
	{p_end}


{title:Description}

{pstd}
{opt truncreg} fits a regression model of {depvar} on {varlist} from a sample
drawn from a restricted part of the population.  Under the normality
assumption for the whole population, the error terms in the truncated
regression model have a truncated normal distribution, which is a normal
distribution that has been scaled upward so that the distribution integrates
to one over the restricted range.


{title:Options}

{dlgtab:Model}

{phang}
{opt noconstant}; see {help estimation options##noconstant:estimation options}.

{phang}
{cmd:ll(}{varname}|{it:#}{cmd:)} and
{opt ul(varname|#)} indicate the upper and lower limits for truncation,
respectively.  You may specify one or both.
Observations with {it:depvar} {ul:<} {opt ll()} are left-truncated,
observations with {it:depvar} {ul:>} {opt ul()} are right-truncated,
and the remaining observations are not truncated.
See {helpb tobit} for a more detailed description.

{dlgtab:Model 2}

{phang}
{opth offset(varname)}; see {help estimation options##offset():estimation options}.

{phang}
{opt marginal} estimates the marginal effects in the
   subpopulation.  You may specify {opt marginal} when you fit the model or
   redisplay the results.

{phang}
{opt at(matname)} specifies the point at which to estimate the marginal
effects. The default is to estimate the effects at the means of the
independent variables, where the means are computed over the subpopulation of
observations that are not truncated.  If there are k independent variables,
{it:matname} should be 1 x k.  You can specify {opt at()} when you fit the
model or redisplay the results.

{pmore}
{opt at()} implies {opt marginal}; specifying {cmd:marginal at()} is the
equivalent to typing {opt at()} by itself.

{phang}
{opt constraints(constraints)}; see {help estimation options##constraints():estimation options}.

{dlgtab:SE/Robust}

{phang}
{opth vce(vcetype)}; see {it:{help vce_option}}.

{phang}
{opt robust}, {opth cluster(varname)}; see {help estimation options##robust:estimation options}.

{dlgtab:Reporting}

{phang}
{opt level(#)}; see {help estimation options}.

{phang}
{opt noskip} specifies that a full maximum-likelihood model with only a
   constant for the regression equation be fitted.  This model is not
   displayed, but is used as the base model to compute a likelihood-ratio test
   for the model test statistic displayed in the estimation header.  By
   default, the overall model test statistic is an asymptotically equivalent
   Wald test of all the parameters in the regression equation being zero
   (except the constant).  For many models, this option can substantially
   increase estimation time.

{marker maximize_options}{...}
{dlgtab:Max options}

{phang}
{it:maximize_options}:
{opt diff:icult},
{opt tech:nique(algorithm_spec)},
{opt iter:ate(#)},
[{cmdab:no:}]{opt lo:g},
{opt tr:ace},
{opt grad:ient},
{opt showstep},
{opt hess:ian},
{opt shownr:tolerance},
{opt tol:erance(#)},
{opt ltol:erance(#)},
{opt gtol:erance(#)},
{opt nrtol:erance(#)},
{opt nonrtol:erance(#)},
{opt from(init_specs)};
see {help maximize}.  These options are seldom used, but you may use the
{opt ltol(#)} option to relax the convergence criterion; the default is
{cmd:1e-6} during specification searches.


{title:Examples}

{phang}{cmd:. truncreg price mpg for, ll(4000) ul(10000)}{p_end}
{phang}{cmd:. truncreg, marginal}{p_end}
{phang}{cmd:. mat B=(25,1)}{p_end}
{phang}{cmd:. truncreg, marginal at(B)}


{title:Also see}

{psee}
Manual:  {bf:[R] truncreg}

{psee}
Online:  {help truncreg postestimation};{break}
{helpb constraint},
{helpb tobit}
{p_end}