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- W3022924870 abstract "Identifying the sub-population structures along with the tailored treatments for all groups plays a critical rule for assigning the best available treatment to an individual patient. Subgroup analysis, a key to develop personalized medicine, becomes increasingly important over the past decade. Besides frequentist methods, there are a spectrum of methods developed from Bayesian perspectives to identify subgroups. In this chapter, we provide a comprehensive overview of Bayesian methods and discuss their properties. We further examine empirical performance of the two Bayesian methods via simulation studies and a real data analysis." @default.
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- W3022924870 date "2020-01-01" @default.
- W3022924870 modified "2023-09-23" @default.
- W3022924870 title "Subgroup Analysis from Bayesian Perspectives" @default.
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- W3022924870 doi "https://doi.org/10.1007/978-3-030-40105-4_16" @default.
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