Volume 36, Issue 6
Research Article

A studentized permutation test for three‐arm trials in the ‘gold standard’ design

Tobias Mütze

Corresponding Author

E-mail address: tobias.muetze@med.uni‐goettingen.de

Department of Medical Statistics, University Medical Center Göttingen, Humboldtallee 32, Göttingen, 37073 Germany

Correspondence to: Tobias Mütze, Department of Medical Statistics, University Medical Center Göttingen, Humboldtallee 32, 37073 Göttingen, Germany.

E‐mail: tobias.muetze@med.uni‐goettingen.de

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Frank Konietschke

Department of Medical Statistics, University Medical Center Göttingen, Humboldtallee 32, Göttingen, 37073 Germany

Department of Mathematical Sciences, University of Texas at Dallas, Richardson, 75080 TX, U.S.A.

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Axel Munk

Institute for Mathematical Stochastics, Georg‐August‐University of Göttingen, Goldschmidtstraße 7, Göttingen, 37077 Germany

Max Planck Institute for Biophysical Chemistry, Am Faßberg 11, Göttingen, 37077 Germany

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Tim Friede

Department of Medical Statistics, University Medical Center Göttingen, Humboldtallee 32, Göttingen, 37073 Germany

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First published: 16 November 2016
Citations: 7

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 package ThreeArmedTrials which is available on the comprehensive R archive network (CRAN). Copyright © 2016 John Wiley & Sons, Ltd.

Number of times cited according to CrossRef: 7

  • Noninferiority trials: What's clinically (ir)relevant?, The Journal of Thoracic and Cardiovascular Surgery, 10.1016/j.jtcvs.2020.03.168, (2020).
  • Simultaneous confidence interval for assessing non‐inferiority with assay sensitivity in a three‐arm trial with binary endpoints, Pharmaceutical Statistics, 10.1002/pst.2010, 19, 5, (518-531), (2020).
  • Randomization Tests for Weak Null Hypotheses in Randomized Experiments, Journal of the American Statistical Association, 10.1080/01621459.2020.1750415, (1-16), (2020).
  • Sequential parallel comparison design for “gold standard” noninferiority trials with a prespecified margin, Biometrical Journal, 10.1002/bimj.201800394, 61, 6, (1493-1506), (2019).
  • The association of TNF-α −308G/A and −238G/A polymorphisms with type 2 diabetes mellitus: a meta-analysis, Bioscience Reports, 10.1042/BSR20191301, 39, 12, (2019).
  • Group sequential designs for negative binomial outcomes, Statistical Methods in Medical Research, 10.1177/0962280218773115, (096228021877311), (2018).
  • Blinded sample size re‐estimation in three‐arm trials with ‘gold standard’ design, Statistics in Medicine, 10.1002/sim.7356, 36, 23, (3636-3653), (2017).

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