Main content

Ordinal Regression Models in Psychology: A Tutorial  /

Date created: | Last Updated:

: DOI | ARK

Creating DOI. Please wait...

Create DOI

Category: Project

Description: Ordinal variables, while extremely common in Psychology, are almost exclusively analysed with statistical models that falsely assume them to be metric. This practice can lead to distorted effect size estimates, inflated error rates, and other problems. We argue for the application of ordinal models that make appropriate assumptions about the variables under study. In this tutorial article, we first explain the three major ordinal model classes; the cumulative, sequential and adjacent category models. We then show how to fit ordinal models in a fully Bayesian framework with the R package brms, using data sets on stem cell opinions and marriage time courses. Appendices provide detailed mathematical derivations of the models and a discussion of censored ordinal models. Ordinal models provide better theoretical interpretation and numerical inference from ordinal data, and we recommend their widespread adoption in Psychology.

License: CC-By Attribution 4.0 International

Has supplemental materials for Ordinal Regression Models in Psychology: A Tutorial on PsyArXiv

Files

Loading files...

Citation

Tags

Recent Activity

Loading logs...