oprobit — Ordered probit regression - Data Analysis and ...
Ordered probit regressionDescriptionQuick startMenuSyntaxOptionsRemarks and examplesStored resultsMethods and formulasReferencesAlso seeDescriptionoprobitfits Ordered probit models of ordinal variabledepvaron the independent variablesindepvars. The actual values taken on by the dependent variable are irrelevant, except that largervalues are assumed to correspond to higher startOrdinal probit model ofyonx1and categorical variablesaandboprobit y x1 ofyonx1and a one-period lagged value ofx1usingtssetdataoprobit y x1 above, but calculate results for each level ofcatvarand save statistics , by(catvar) saving(myfile): oprobit y x1 >Ordinal outcomes> Ordered probit regression12 oprobit Ordered probit regressionSyntaxoprobitdepvar[indepvars] [if][in][weight][,options]optionsDescrip tionModeloffset(varname)includevarnamein model with coefficient constrained to 1constraints(constraints)apply specified linear constraintscollinearkeep collinear variablesSE/Robustvce(vcetype)vcetypemay beoim,robust,clusterclustvar,bootstrap, orjackknifeReportinglevel(#)set confidence level; default islevel(95)nocnsreportdo not di
6oprobit— Ordered probit regression Methods and formulas See Methods and formulas of[R] ologit.References Aitchison, J., and S. D. Silvey. 1957. The generalization of probit analysis to the case of multiple responses.
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