OGLM: Stata module to estimate Ordinal Generalized Linear Models. oglm estimates Ordinal Generalized Linear Models. It supports several link functions, including logit, probit, complementary log-log, log-log and cauchit. When an ordinal regression model incorrectly assumes that error variances are the same for all cases, the standard errors are wrong and (unlike OLS regression) the parameter estimates are biased. With oglm you can estimate heterogeneous choice/ location-scale models that explicitly specify the determinants of heteroskedasticity in an attempt to understand and correct for it. Several other special cases of ordinal generalized linear models can also be estimated by oglm. oglm was inspired by the SPSS PLUM routine but differs somewhat in its terminology, labeling of links, and the variables that are allowed when modeling heteroskedasticity. Stata 9 or 10 users should use oglm9 instead.

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  1. Fullerton, Andrew S.; Xu, Jun: Ordered regression models. Parallel, partial, and non-parallel alternatives (2016)