Journal
JOURNAL OF BIOPHARMACEUTICAL STATISTICS
Volume 29, Issue 6, Pages 1082-1102Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/10543406.2019.1584204
Keywords
GUIDE; interaction tree; qualitative interaction trees; T-AIC/T-BIC; virtual twins
Categories
Funding
- NIH [P01CA142538, GM70335]
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Subgroup analysis, as the key component of personalized medicine development, has attracted a lot of interest in recent years. While a number of exploratory subgroup searching approaches have been proposed, informative evaluation criteria and scenario-based systematic comparison of these methods are still underdeveloped topics. In this article, we propose two evaluation criteria in connection with traditional type I error and power concepts, and another criterion to directly assess recovery performance of the underlying treatment effect structure. Extensive simulation studies are carried out to investigate empirical performance of a variety of tree-based exploratory subgroup methods under the proposed criteria. A real data application is also included to illustrate the necessity and importance of method evaluation.
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