Ordinal regression modelling between proportional odds and non-proportional odds
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A Comparison of McCullagh’s Proportional Odds Model to Modern Ordinal Regression Algorithms
We introduce McCullagh’s Proportional Odds as the foundation for modern Ordinal Regression approaches. Proportional Odds introduced the ideas of (1) mapping examples to the real number line, and (2) segmenting the real number line using a set of thresholds. We compare against two modern approaches to Ordinal Regression which use the framework established by Proportional Odds and find some surpr...
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Researchers have a variety of options when choosing statistical software packages that can perform ordinal logistic regression analyses. However, statistical software, such as Stata, SAS, and SPSS, may use different techniques to estimate the parameters. The purpose of this article is to (1) illustrate the use of Stata, SAS and SPSS to fit proportional odds models using educational data; and (2...
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