A studentized permutation test for three‐arm trials in the 'gold standard' design. (16th November 2016)

• Record Type: Journal Article
• Authors: Mütze, Tobias; Konietschke, Frank; Munk, Axel; Friede, Tim
• Is Part Of: Statistics in medicine. Volume 36:Number 6(2017)
• Page Start: 883
• Page End: 898
• Publication Date: 2016-11-16
• Subjects: non‐inferiority -- permutation test -- three‐arm trial -- gold standard design -- Wald‐type test; Medical statistics -- Periodicals; Statistique médicale -- Périodiques; Statistiques médicales -- Périodiques; 610.727
• DOI: 10.1002/sim.7176
• Languages: English
• ISSNs: 0277-6715

Abstract

Abstract : The 'gold standard' design for three‐arm trials refers to trials with an active control and a placebo control in addition to the experimental treatment group. This trial design is recommended when being ethically justifiable and it allows the simultaneous comparison of experimental treatment, active control, and placebo. Parametric testing methods have been studied plentifully over the past years. However, these methods often tend to be liberal or conservative when distributional assumptions are not met particularly with small sample sizes. In this article, we introduce a studentized permutation test for testing non‐inferiority and superiority of the experimental treatment compared with the active control in three‐arm trials in the 'gold standard' design. The performance of the studentized permutation test for finite sample sizes is assessed in a Monte Carlo simulation study under various parameter constellations. Emphasis is put on whether the studentized permutation test meets the target significance level. For comparison purposes, commonly used Wald‐type tests, which do not make any distributional assumptions, are included in the simulation study. The simulation study shows that the presented studentized permutation test for assessing non‐inferiority in three‐arm trials in the 'gold standard' design outperforms its competitors, for instance the test based on a quasi‐Poisson model, for count data. The methods discussed in this paper are implemented in the R packageThreeArmedTrials which is available on the comprehensive R archive network (CRAN). Copyright © 2016 John Wiley & Sons, Ltd.