Notes on testing noninferiority in multivariate binary data under the matched-pair design. (August 2016)

• Record Type: Journal Article
• Authors: Lui, Kung-Jong; Chang, Kuang-Chao
• Other Names: Lawson Andrew B guest-editor.; Lee Duncan guest-editor.; MacNab Ying guest-editor.
• Is Part Of: Statistical methods in medical research. Volume 25:Number 4(2016:Aug.)
• Page Start: 1272
• Page End: 1289
• Publication Date: 2016-08
• Subjects: Odds ratio -- multivariate binary data -- matched-pairs -- noninferiority -- exact test -- bootstrapping; Medicine -- Research -- Statistical methods -- Periodicals; Research -- Periodicals; Review Literature -- Periodicals; Statistics -- methods -- Periodicals; Médecine -- Recherche -- Méthodes statistiques -- Périodiques; 610.727
• DOI: 10.1177/0962280213477022
• Languages: English
• ISSNs: 0962-2802

Abstract

Since therapeutic efficacy is often measured by multiple endpoints, it will be of use if one can incorporate the information on various variables of response into procedures for testing noninferiority to improve power of a univariate test procedure for each individual variable. On the basis of the proposed mixed effects logistic regression model for multivariate binary data under the matched-pairs design, we develop procedures for testing noninferiority with respect to the odds ratio in multivariate binary data under the matched-pair design. We discuss use of Bonferroni's and Scheffe's methods to control the inflation in Type I error due to multiple tests. We further employ Monte Carlo simulation to evaluate and compare the performance of these test procedures. Finally, we use the data taken from a crossover clinical trial that monitored several adverse events of an antidepressive drug to illustrate the use of test procedures derived here.