文章基本信息

标题：Generalized ordered logit/partial proportional odds models for ordinal dependent variables
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作者：Williams, Richard A.
期刊名称：Journal of Food Distribution Research
印刷版ISSN：0047-245X
出版年度：2006
卷号：37
期号：SUPPL
页码：58-82
出版社：Food Distribution Research Society
摘要：This article describes the gologit2 program for generalized ordered logit models. gologit2 is inspired by Vincent Fu’s gologit routine (Stata Technical Bulletin Reprints 8: 160–164) and is backward compatible with it but offers several additional powerful options. A major strength of gologit2 is that it can fit three special cases of the generalized model: the proportional odds/parallel-lines model, the partial proportional odds model, and the logistic regression model. Hence, gologit2 can fit models that are less restrictive than the parallel-lines models fitted by ologit (whose assumptions are often violated) but more parsimonious and interpretable than those fitted by a nonordinal method, such as multinomial logistic regression (i.e., mlogit). Other key advantages of gologit2 include support for linear constraints, survey data estimation, and the computation of estimated probabilities via the predict command.
关键词：gologit2;gologit;logistic regression;ordinal regression;proportional odds;partial proportional odds;generalized ordered logit model;parallel-lines model