Identifying treatment effect heterogeneity in dose‐finding trials using Bayesian hierarchical models-Reference-Cited by-同舟云学术

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Identifying treatment effect heterogeneity in dose‐finding trials using Bayesian hierarchical models

Published:2021-07-13 Issue:1 Volume:21 Page:17-37
ISSN:1539-1604
Container-title:Pharmaceutical Statistics
language:en
Short-container-title:Pharmaceutical Statistics

Author:

Thomas Marius¹^ORCID,Bornkamp Björn¹^ORCID,Ickstadt Katja²

Affiliation:

1. Clinical Development and Analytics Novartis Pharma AG Basel Switzerland

2. Faculty of Statistics TU Dortmund University Dortmund Germany

Funder

H2020 Marie Skłodowska-Curie Actions

Staatssekretariat für Bildung, Forschung und Innovation

Publisher

Wiley

Subject

Pharmacology (medical),Pharmacology,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/pst.2150

Reference31 articles.

1. Personalized Medicine: Four Perspectives of Tailored Medicine

2. Distinguishing prognostic and predictive biomarkers: an information theoretic approach;Sechidis K;Bioinformatics,2018

3. Subgroup analysis via recursive partitioning;Su X;J Mach Learn Res,2009

4. Subgroup identification from randomized clinical trial data

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

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Predicting subgroup treatment effects for a new study: Motivations, results and learnings from running a data challenge in a pharmaceutical corporation;Pharmaceutical Statistics;2024-02-07

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