Goodness-of-fit tests for ordinal response regression models

• Published in: Statistics in medicine 2004-03, Vol.23 (6), p.999-1014
• Main Authors: Pulkstenis, Erik, Robinson, Timothy J.
• Format: Article
• Language: English
• Subjects: Aortic Aneurysm, Abdominal - surgery; Chi-Square Distribution; deviance; Female; goodness-of-fit; Hemorrhage; Humans; Logistic Models; logistic regression; Male; ordinal response; proportional oddsmodel; Regression Analysis; The Pearson chi-square
• ISSN: 0277-6715; 1097-0258
• DOI: 10.1002/sim.1659

It is well documented that the commonly used Pearson chi‐square and deviance statistics are not adequate for assessing goodness‐of‐fit in logistic regression models when continuous covariates are modelled. In recent years, several methods have been proposed which address this shortcoming in the binary logistic regression setting or assess model fit differently. However, these techniques have typically not been extended to the ordinal response setting and few techniques exist to assess model fit in that case. We present the modified Pearson chi‐square and deviance tests that are appropriate for assessing goodness‐of‐fit in ordinal response models when both categorical and continuous covariates are present. The methods have good power to detect omitted interaction terms and reasonable power to detect failure of the proportional odds assumption or modelling the wrong functional form of a continuous covariate. These tests also provide immediate information as to where a model may not fit well. In addition, the methods are simple to understand and implement, and are non‐specific. That is, they do not require prespecification of a type of lack‐of‐fit to detect. Copyright © 2004 John Wiley & Sons, Ltd.