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• W2921398811 abstract "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." @default.
• W2921398811 created "2019-03-22" @default.
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• W2921398811 date "2019-03-12" @default.
• W2921398811 modified "2023-09-30" @default.
• W2921398811 title "Look before you leap: systematic evaluation of tree-based statistical methods in subgroup identification" @default.
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• W2921398811 doi "https://doi.org/10.1080/10543406.2019.1584204" @default.
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