{smcl} {* 04Sep2006}{...} {cmd:help bioprobit} {hline} {title:Title} {p2colset 5 20 22 2}{...} {p2col :{hi: bioprobit} {hline 2}}Bivariate ordered probit regression{p_end} {p2colreset}{...} {title:Syntax} {phang}Bivariate ordered probit model {p 8 17 2} {cmd:bioprobit} {it:{help depvar:depvar1} depvar2} {varlist} {ifin} {weight} [{cmd:,} {it:{help bioprobit##options:options}}] {phang}Simultaneous bivariate ordered probit model {p 8 17 2} {cmd:bioprobit} ({it:{help depvar:depvar1}} [=] {varlist:1}) ({it:{help depvar:depvar2}} [=] {varlist:2}) {ifin} {weight} [{cmd:,} {it:{help bioprobit##options:options}}] {title:Syntax for predict} {p 8 16 2} {cmd:predict} {dtype} {it:{help newvar}} {ifin} [{cmd:,} {it:statistic} {opt o:utcome(outcome pair)} {opt nooff:set}] {synoptset 11 tabbed}{...} {synopthdr :statistic} {synoptline} {syntab :Main} {synopt :{opt xb1}} fitted values for equation 1{p_end} {synopt :{opt xb2}} fitted values for equation 2{p_end} {synopt :{opt stdp1}} standard error of fitted values for equation 1{p_end} {synopt :{opt stdp2}} standard error of fitted values for equation 2{p_end} {synoptline} {p2colreset}{...} {synoptset 20 tabbed}{...} {marker options}{...} {synopthdr} {synoptline} {syntab :Model} {synopt :{opth off:set1(varname)}} offset variable for first equation{p_end} {synopt :{opth off:set2(varname)}} offset variable for second equation{p_end} {synopt :{opt col:linear}} keep collinear variables {syntab :SE/Robust} {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} {syntab :Max option} {synopt :{it:{help bioprobit##maximize_options:maximize_options}}}control the maximization process;{p_end} {synoptline} {p2colreset}{...} {p 4 6 2} {opt fweight}s, {opt iweight}s, and {opt pweight}s are allowed;see {help weight}.{p_end} {title:Description} {pstd} {opt bioprobit} fits maximum-likelihood two-equation ordered probit models of ordinal variables {depvar:1} and {depvar:2} on the independent variables {indepvars:1} and {indepvars:2}. The actual values taken on by dependent variables are irrelevant, except that larger values are assumed to correspond to "higher" outcomes. //Up to 50 outcomes are allowed in Stata/SE and Intercooled Stata, and up to 20 outcomes in Small Stata//. {pstd} See {help logistic estimation commands} for a list of related estimation commands. {title:Options} {dlgtab:Model} {phang} {opth offset1(varname)}, {opth offset2(varname)}, {opt collinear}; see {help estimation options}. {dlgtab:Options} {phang} {opt robust}, {opth cluster(varname)}; see {help estimation options}. {opt cluster()} can be used with {opt pweight}s to produce estimates for unstratified cluster-sampled data. {dlgtab:Reporting} {phang} {opt level(#)}; see {help estimation options}. {marker maximize_options}{...} {dlgtab:Max options} {phang} {it:maximize_options}: {opt tech:nique(algorithm_spec)}, {opt iter:ate(#)}, [{cmdab:no:}]{opt lo:g}, {opt tr:ace}, {opt hess:ian}, {opt grad:ient}, {opt showstep}, {opt tol:erance(#)}, {opt ltol:erance(#)}, {opt gtol:erance(#)}, {opt nrtol:erance(#)}, {opt nonrtol:erance}, {opt from(init_specs)}; see {help maximize}. {title:Options for predict} {phang} {opt xb1} calculates the linear prediction for equation 1. {phang} {opt xb2} calculates the linear prediction for equation 2. {phang} {opt stdp1} calculates the standard error of the linear prediction of equation 1. {phang} {opt stdp2} calculates the standard error of the linear prediction of equation 2. {phang} {opt outcome(outcome pair)} specifies for which outcome pair the predicted probabilities are to be calculated. {opt outcome()} should contain pair of either values of the dependent variables or one of {opt #1}, {opt #2}, {it:...}, with {opt #1} meaning the first category of a dependent variable, {opt #2} the second category, etc. If one of the arguments is missing then result will be the marginal probability, i.e. {opt outcome(., k)} wil retun Pr(y2=k) {phang} {opt nooffset} is relevant only if you specified {opth offset1(varname)} or {opt offset2(varname)} for {cmd:bioprobit}. It modifies the calculations made by {opt predict} so that they ignore the offset variables; the linear predictions are treated as xb1 rather than xb1 + offset1 and xb2 rather than as xb2 + offset2. {title:Examples} {phang}{cmd:. bioprobit headroom foreign price length mpg turn}{p_end} {title:Also see} {psee} Online: {helpb biprobit}, {helpb oprobit}, {helpb ml}{p_end}