Generalized Ordered Logit/Partial Proportional Odds Models for Ordinal Dependent Variables

University of Notre Dame

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Abstract

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…

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Topics & keywords

Keywords
  • Multinomial logistic regression
  • Ordered logit
  • Odds
  • Ordinal regression
  • Logistic regression
  • Logit
  • Ordinal data
  • Mathematics
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