Fitting Proportional Odds Models to Educational Data with Complex Sampling Designs in Ordinal Logistic Regression

Ordinal regression modelling between proportional odds and non-proportional odds

Fitting Stereotype Logistic Regression Models for Ordinal Response Variables in Educational Research (Stata)

The stereotype logistic (SL) model is an alternative to the proportional odds (PO) model for ordinal response variables when the proportional odds assumption is violated. This model seems to be underutilized. One major reason is the constraint of current statistical software packages. Statistical Package for the Social Sciences (SPSS) cannot perform the SL regression analysis, and SAS does not ...

repolr: An R Package for Fitting Proportional-odds Models to Repeated Ordinal Scores

Modelling repeated ordinal score data is a common statistical problem, across many application areas. The proportional-odds model is widely applied to such repeated ordinal scores and can be fitted in the repolr package (repeated measures proportional odds logistic regression) in R using the method of generalized estimating equations (GEE). The GEE approach specifies a model for the mean of the...

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...

Proportional Odds and Partial Proportional Odds Models for Ordinal Response Variables