title: Pairwise comparisons with ordered categorical data.
abstract: 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.
authors: School of Management, Fuzhou University, Fuzhou, China.
authors: Yueqiong
authors: Y
authors: Lin
authors: Siu Hung
authors: SH
authors: Cheung
authors: Wai-Yin
authors: WY
authors: Poon
authors: Tong-Yu
authors: TY
authors: Lu
mesh_terms: D015760:Alfentanil / Q000494:pharmacology; D002648:Child; D002675:Child, Preschool; D002986:Clinical Trials as Topic / Q000379:methods*; D003198:Computer Simulation; D006801:Humans; D016015:Logistic Models; D010146:Pain / Q000188:drug therapy; D010880:Piperidines / Q000494:pharmacology; D015742:Propofol / Q000009:adverse effects; D000077208:Remifentanil
chemical_list: D010880:Piperidines; D015760:Alfentanil; D000077208:Remifentanil; D015742:Propofol
keywords: familywise error rate; latent variable model; log-odds ratio; ordered categorical response; proportional odds model