Discussion on “Optimal Test Procedures for Multiple Hypotheses Controlling the Familywise Expected Loss” by Willi Maurer, Frank Bretz, and Xiaolei Xun
Affiliation:
1. Mathematics and Computer Science, Competence Center for Clinical Trials Bremen, University of Bremen , Bremen , Germany
Abstract
Abstract
This comment builds on the familywise expected loss (FWEL) framework suggested by Maurer, Bretz, and Xun in 2022. By representing the populationwise error rate (PWER) as FWEL, it is illustrated how the FWEL framework can be extended to clinical trials with multiple and overlapping populations and the PWER can be generalized to more general losses. The comment also addresses the question of how to deal with midtrial changes in the posttrial risks and related losses that are caused by data-driven decisions. Focusing on multiarm trials with the possibility of dropping treatments midtrial, we suggest to switch from control of the unconditional expected loss to control of the conditional expected loss that is related to the actual risks and is conditional on the sample event that causes the change in the risks. The problem and here suggested solution is also motivated with a sequence of independent trials for a hitherto incurable disease which ends when an efficient treatment is found. No multiplicity adjustment is applied in this case and we show how this can be justified by the consideration of the changing out-trial risks and with control of conditional type I error rates and losses.
Funder
Bundesministerium für Bildung und Forschung
Publisher
Oxford University Press (OUP)
Subject
Applied Mathematics,General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,Statistics and Probability
Reference3 articles.
1. The population-wise error rate for clinical trials with overlapping populations;Brannath;Statistical Methods in Medical Research,2023
2. Optimal test procedures for multiple hypotheses controlling the familywise expected loss;Maurer,2023
3. The Multivariate Normal Distribution
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