{smcl} {* *! version 1.0.0 3mar2014}{...} {cmd: help treatoprobit} {right:also see: {help treatoprobit postestimation}} {hline} {title:Treatment Effects Ordered Probit} {phang} {bf: treatoprobit} {hline 2} Estimate effect of binary treatment on discrete, ordered outcome. {title:Syntax} {p 8 17 2} {cmdab:treatoprobit} y_ordered x_ordered {ifin} {weight} {cmd:, treat} (y_treat x_treat) [{it: options}] {synoptset 20 tabbed}{...} {synopthdr} {synoptline} {syntab: Main} {synopt:{opt c:luster(varname)}} cluster standard errors using {it:varname} {p_end} {synopt:{opt r:obust}} compute robust variance covariance matrix / standard errors {p_end} {synoptline} {p 4 6 2} {cmd: pweight, iweight, aweight}s are allowed; see {help weight} {title:Description} {pstd} {cmd:treatoprobit} estimates a model in which {cmd:treat} is a binary indicator for a treatment ({it:y_treat}) for which selection is believed correlated with the outcome of interest, {it: y_ordered}. The model assumes that the unobservables in treatment and outcome equations have a bivariate normal distribution. Parameters of the model are estimated by maximum likelihood. {title:Examples} {phang} Let self assessed health {bf: SAH} be ordered on a 1-5 scale (excellent, very good, good, fair, poor), and {bf:medicaid} be an indicator of participation in Medicaid: {p_end} {cmd:. use nhisdataex, clear} {phang}{cmd:. treatoprobit sah female married, treat(medicaid female married)} {phang}{cmd:. treatoprobit sah female married [pweight=weight], treat(medicaid female married) vce(robust)} {smcl} {title:Author} {pstd} Christian A. Gregory, Economic Research Service, USDA, cgregory@ers.usda.gov