Generalized Ordered Logit/Partial Proportional Odds Models for Ordinal Dependent Variables
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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
- Multinomial logistic regression
- Ordered logit
- Odds
- Ordinal regression
- Logistic regression
- Logit
- Ordinal data
- Mathematics
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