Literature DB >> 21225894

A Bayesian subgroup analysis with a zero-enriched Polya Urn scheme.

S Sivaganesan1, Purushottam W Laud, Peter Müller.   

Abstract

We introduce a new approach to inference for subgroups in clinical trials. We use Bayesian model selection, and a threshold on posterior model probabilities to identify subgroup effects for reporting. For each covariate of interest, we define a separate class of models, and use the posterior probability associated with each model and the threshold to determine the existence of a subgroup effect. As usual in Bayesian clinical trial design we compute frequentist operating characteristics, and achieve the desired error probabilities by choosing an appropriate threshold(s) for the posterior probabilities. 2010 John Wiley & Sons, Ltd.

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Year:  2010        PMID: 21225894     DOI: 10.1002/sim.4108

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  10 in total

Review 1.  Bayesian Approaches to Subgroup Analysis and Related Adaptive Clinical Trial Designs.

Authors:  Ciara Nugent; Wentian Guo; Peter Müller; Yuan Ji
Journal:  JCO Precis Oncol       Date:  2019-10-24

2.  Look before you leap: systematic evaluation of tree-based statistical methods in subgroup identification.

Authors:  Yang Liu; Xiwen Ma; Donghui Zhang; Lijiang Geng; Xiaojing Wang; Wei Zheng; Ming-Hui Chen
Journal:  J Biopharm Stat       Date:  2019-03-12       Impact factor: 1.051

3.  A nonparametric Bayesian basket trial design.

Authors:  Yanxun Xu; Peter Müller; Apostolia M Tsimberidou; Donald Berry
Journal:  Biom J       Date:  2018-05-28       Impact factor: 2.207

4.  A subgroup cluster-based Bayesian adaptive design for precision medicine.

Authors:  Wentian Guo; Yuan Ji; Daniel V T Catenacci
Journal:  Biometrics       Date:  2016-10-24       Impact factor: 2.571

5.  Bayesian population finding with biomarkers in a randomized clinical trial.

Authors:  Satoshi Morita; Peter Müller
Journal:  Biometrics       Date:  2017-03-03       Impact factor: 2.571

6.  Nonparametric Bayesian Bi-Clustering for Next Generation Sequencing Count Data.

Authors:  Yanxun Xu; Juhee Lee; Yuan Yuan; Riten Mitra; Shoudan Liang; Peter Müller; Yuan Ji
Journal:  Bayesian Anal       Date:  2013-12       Impact factor: 3.728

7.  A Nonparametric Bayesian Model for Local Clustering with Application to Proteomics.

Authors:  Juhee Lee; Peter Müller; Yitan Zhu; Yuan Ji
Journal:  J Am Stat Assoc       Date:  2013-01-01       Impact factor: 5.033

Review 8.  Subgroup analyses in confirmatory clinical trials: time to be specific about their purposes.

Authors:  Julien Tanniou; Ingeborg van der Tweel; Steven Teerenstra; Kit C B Roes
Journal:  BMC Med Res Methodol       Date:  2016-02-18       Impact factor: 4.615

Review 9.  Methods for identification and confirmation of targeted subgroups in clinical trials: A systematic review.

Authors:  Thomas Ondra; Alex Dmitrienko; Tim Friede; Alexandra Graf; Frank Miller; Nigel Stallard; Martin Posch
Journal:  J Biopharm Stat       Date:  2016       Impact factor: 1.051

10.  CAPITAL: Optimal subgroup identification via constrained policy tree search.

Authors:  Hengrui Cai; Wenbin Lu; Rachel Marceau West; Devan V Mehrotra; Lingkang Huang
Journal:  Stat Med       Date:  2022-07-07       Impact factor: 2.497

  10 in total

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