Ordinal Regression Analysis: Fitting the Proportional Odds Model Using Stata, SAS and SPSS

Ordinal Regression Analysis: Fitting the Proportional Odds Model Using Stata, SAS and SPSS

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...

Ordinal regression modelling between proportional odds and non-proportional odds

177-30: Using SAS® to Estimate Proportional Odds Ratio Model for Meta-Analysis of Diagnostic Tests

This work shows how we can use SAS system to implement the proportional odds ratio (POR) model (Siadaty 2004). POR is used to pool results of several studies together in a meta-analysis of diagnostic tests. It generalizes comparison of competing tests when there are two or more tests available for disease and each test has been studied in one or more papers and each paper might have studied mor...

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...

Proportional Odds and Partial Proportional Odds Models for Ordinal Response Variables