📄 y_e_probit.hlp
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{smcl}
{p 0 4}
{help contents:Top}
> {help y_stat:Statistics}
> {help y_est:Estimation}
> {help y_est0:Regression models}
> {help y_e_bin:Binary outcome data}
{bind:> {bf:Probit}}
{p_end}
{hline}
{title:Help and category listings}
{p 4 8 4}
{bf:{help probit:Probit estimation command}}{break}
maximum-likelihood probit estimation, but also click below for more
{p 4 8 4}
{bf:{help probit_postestimation:Postestimation commands for use after probit}}{break}
classification table, goodness-of-fit test, ROC curve,
graphs ... after probit
{p 4 8 4}
{bf:{help hetprob:Heteroskedastic probit estimation}}{break}
maximum-likelihood heteroskedastic probit model
{p 4 8 4}
{bf:{help glogit:Probit estimation on grouped data}}{break}
probit on grouped (blocked) data; weighted least-squares probit
{p 4 8 4}
{bf:{help biprobit:Bivariate probit models}}{break}
including seemingly unrelated bivariate probit model
{p 4 8 4}
{bf:{help ivprobit:Probit model with endogenous regressors}}{break}
maximum-likelihood or Newey's minimum chi-squared estimator
INCLUDE help ypostnote
{hline}
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