Value Function Guided Subgroup Identification via Gradient Tree Boosting: a Framework to Handle Multiple Outcomes for Optimal Treatment Recommendation

Pingye Zhang, Peng Liu, Junshui Ma & Yue Shentu
In randomized clinical trials, there has been an increasing interest in identifying subgroups with heterogeneous responses to study treatment based on baseline patient characteristics. Even though the benefit risk assessment of any patient population or subgroups is almost always a multi-facet consideration, the statistical literature of subgroup identification has largely been limited to a single clinical outcome. In the paper, we propose a nonparametric method that searches for subgroup membership scores by maximizing a value...
1 citation reported since publication in 2021.
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