Learning and confirming a class of treatment responders in clinical trials

Metalearners for estimating heterogeneous treatment effects using machine learning

(2019) Sören R. Künzel et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Generalized random forests

(2019) Susan Athey et al.   ANNALS OF STATISTICS

A comparison of subgroup identification methods in clinical drug development: Simulation study and regulatory considerations

(2019) Cynthia Huber et al.   PHARMACEUTICAL STATISTICS

Subgroup identification for precision medicine: A comparative review of 13 methods

(2019) Wei‐Yin Loh et al.   Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery

Cross-Screening in Observational Studies That Test Many Hypotheses

(2018) Qingyuan Zhao et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

Estimation and Inference of Heterogeneous Treatment Effects using Random Forests

(2018) Stefan Wager et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

Some methods for heterogeneous treatment effect estimation in high dimensions

(2018) Scott Powers et al.   STATISTICS IN MEDICINE

Multiplicity issues in exploratory subgroup analysis

(2017) Ilya Lipkovich et al.   Journal of Biopharmaceutical Statistics

Model-Based Recursive Partitioning for Subgroup Analyses

(2016) Heidi Seibold et al.  

Recursive partitioning for heterogeneous causal effects: Table 1.

(2016) Susan Athey et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Tutorial in biostatistics: data-driven subgroup identification and analysis in clinical trials

(2016) Ilya Lipkovich et al.   STATISTICS IN MEDICINE

Model-Based Recursive Partitioning for Subgroup Analyses

(2016) Heidi Seibold et al.   International Journal of Biostatistics

A predictive enrichment procedure to identify potential responders to a new therapy for randomized, comparative controlled clinical studies

(2015) Junlong Li et al.   BIOMETRICS

A regression tree approach to identifying subgroups with differential treatment effects

(2015) Wei-Yin Loh et al.   STATISTICS IN MEDICINE

Strategies for Identifying Predictive Biomarkers and Subgroups with Enhanced Treatment Effect in Clinical Trials Using SIDES

(2014) Ilya Lipkovich et al.   Journal of Biopharmaceutical Statistics

Effectively Selecting a Target Population for a Future Comparative Study

(2013) Lihui Zhao et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

Utilizing the integrated difference of two survival functions to quantify the treatment contrast for designing, monitoring, and analyzing a comparative clinical study

(2012) Lihui Zhao et al.   Clinical Trials

Performance guarantees for individualized treatment rules

(2011) Min Qian et al.   ANNALS OF STATISTICS

Decision trees for uplift modeling with single and multiple treatments

(2011) Piotr Rzepakowski et al.   KNOWLEDGE AND INFORMATION SYSTEMS

Subgroup identification based on differential effect search-A recursive partitioning method for establishing response to treatment in patient subpopulations

(2011) Ilya Lipkovich et al.   STATISTICS IN MEDICINE

Subgroup identification from randomized clinical trial data

(2011) Jared C. Foster et al.   STATISTICS IN MEDICINE

Model-Based Recursive Partitioning

(2008) Achim Zeileis et al.   JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS