1. Group-by-Treatment Interaction Effects in Comparative Bioavailability Studies.
- Author
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Schütz, Helmut, Burger, Divan A., Cobo, Erik, Dubins, David D., Farkás, Tibor, Labes, Detlew, Lang, Benjamin, Ocaña, Jordi, Ring, Arne, Shitova, Anastasia, Stus, Volodymyr, and Tomashevskiy, Michael
- Abstract
Comparative bioavailability studies often involve multiple groups of subjects for a variety of reasons, such as clinical capacity limitations. This raises questions about the validity of pooling data from these groups in the statistical analysis and whether a group-by-treatment interaction should be evaluated. We investigated the presence or absence of group-by-treatment interactions through both simulation techniques and a meta-study of well-controlled trials. Our findings reveal that the test falsely detects an interaction when no true group-by-treatment interaction exists. Conversely, when a true group-by-treatment interaction does exist, it often goes undetected. In our meta-study, the detected group-by-treatment interactions were observed at approximately the level of the test and, thus, can be considered false positives. Testing for a group-by-treatment interaction is both misleading and uninformative. It often falsely identifies an interaction when none exists and fails to detect a real one. This occurs because the test is performed between subjects in crossover designs, and studies are powered to compare treatments within subjects. This work demonstrates a lack of utility for including a group-by-treatment interaction in the model when assessing single-site comparative bioavailability studies, and the clinical trial study structure is divided into groups. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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