Yan Sun : Subgroup Identification based on Quantitative Objectives for Randomized and Non-Randomized Studies

Posted by Kyunghee Han , part of the Statistics and Data Science Seminar.

At

Oct. 29, 2025, 4:15 p.m.

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636 SEO

Abstract

Precision medicine is the future of drug development, and subgroup identification plays a critical role in achieving the goal. In this presentation, we propose a powerful end-to-end solution squant (available on CRAN) that explores a sequence of quantitative objectives. The method converts the original study to an artificial 1:1 randomized trial, and features a flexible objective function, a stable signature with good interpretability, and an embedded false discovery rate (FDR) control. We demonstrate its performance through simulation and provide a real data example.