Step-up testing procedure for multiple comparisons with a control for a latent variable model with ordered categorical responses

Publication Type

Journal Article

Publication Date

9-2014

Abstract

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.

Keywords

familywise error rate, latent normal variable model, ordered categorical response, sample size determination

Discipline

Econometrics | Economics | Medicine and Health Sciences

Research Areas

Econometrics

Publication

Statistics in Medicine

Volume

33

Issue

21

First Page

3629

Last Page

3638

ISSN

0277-6715

Identifier

10.1002/sim.6190

Publisher

Wiley

Additional URL

https://doi.org/10.1002/sim.6190

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