Step‐up testing procedure for multiple comparisons with a control for a latent variable model with ordered categorical responses. (23rd April 2014)

• Record Type: Journal Article
• Authors: Lin, Yueqiong; Kwong, Koon Shing; Cheung, Siu Hung; Poon, Wai‐Yin
• Is Part Of: Statistics in medicine. Volume 33:Number 21(2014)
• Page Start: 3629
• Page End: 3638
• Publication Date: 2014-04-23
• Subjects: Medical statistics -- Periodicals; Statistique médicale -- Périodiques; Statistiques médicales -- Périodiques; 610.727
• DOI: 10.1002/sim.6190
• Languages: English
• ISSNs: 0277-6715

Abstract

<abstract abstract-type="main" id="sim6190-abs-0001"> <title>Abstract</title> <p id="sim6190-para-0001">In clinical studies, multiple comparisons of several treatments to a control with ordered categorical responses are often encountered. A popular statistical approach to analyzing the data is to use the logistic regression model with the proportional odds assumption. As discussed in several recent research papers, if the proportional odds assumption fails to hold, the undesirable consequence of an inflated familywise type I error rate may affect the validity of the clinical findings. To remedy the problem, a more flexible approach that uses the latent normal model with single‐step and stepwise testing procedures has been recently proposed. In this paper, we introduce a step‐up procedure that uses the correlation structure of test statistics under the latent normal model. A simulation study demonstrates the superiority of the proposed procedure to all existing testing procedures. Based on the proposed step‐up procedure, we derive an algorithm that enables the determination of the total sample size and the sample size allocation scheme with a pre‐determined level of test power before the onset of a clinical trial. A clinical example is presented to illustrate our proposed method. Copyright © 2014 John Wiley &amp; Sons, Ltd.</p> </abstract>