Premium
Pairwise comparisons with ordered categorical data
Author(s) -
Lin Yueqiong,
Cheung Siu Hung,
Poon WaiYin,
Lu TongYu
Publication year - 2013
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.5751
Subject(s) - pairwise comparison , categorical variable , type i and type ii errors , wilcoxon signed rank test , statistics , logistic regression , mathematics , mann–whitney u test , odds , odds ratio , ordered logit , econometrics , computer science
Clinical trials frequently involve pairwise comparisons of different treatments to evaluate their relative efficacy. In this study, we examine methods for conducting pairwise tests of treatments with ordered categorical responses. A modified version of the Wilcoxon–Mann–Whitney test based on a logistic regression model assuming proportional odds is a popular choice for comparing two treatments. This paper discusses the extension of this test to pairwise comparisons involving more than two treatments. However, when the proportional odds assumption is not valid, the Wilcoxon–Mann–Whitney‐type test procedure cannot control the overall type I error rate at the prespecified level of significance. We therefore propose a better strategy in which a latent normal model is employed. We presented a simulated comparative study of power and the overall type I error rate to illustrate the superiority of the latent normal model. Examples are also given for illustrative purposes. Copyright © 2013 John Wiley & Sons, Ltd.