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Uniformly minimum variance conditionally unbiased estimation in multi-arm multi-stage clinical trials

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Stallard, Nigel and Kimani, Peter K. (2018) Uniformly minimum variance conditionally unbiased estimation in multi-arm multi-stage clinical trials. Biometrika, 105 (2). pp. 495-501. doi:10.1093/biomet/asy004

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Official URL: https://doi.org/10.1093/biomet/asy004

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Abstract

Multi-arm multi-stage clinical trials compare several experimental treatments with a control treatment, with poorly performing treatments dropped at interim analyses. This leads to inferential challenges, including the construction of unbiased treatment effect estimators. A number of estimators unbiased conditional on treatment selection have been proposed, but are specific to certain selection
rules, may ignore the comparison to the control and are not all minimum variance. We obtain estimators for treatment effects compared to the control that are uniformly minimum variance unbiased conditional on selection with any specified rule or stopping for futility.

Item Type: Journal Article
Subjects: R Medicine > R Medicine (General)
Divisions: Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School
Library of Congress Subject Headings (LCSH): Clinical trials -- Methodology
Journal or Publication Title: Biometrika
Publisher: Biometrika Trust
ISSN: 1464-3510
Official Date: 1 June 2018
Dates:
DateEvent
1 June 2018Published
28 February 2018Available
7 January 2018Accepted
Volume: 105
Number: 2
Page Range: pp. 495-501
DOI: 10.1093/biomet/asy004
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
MR/N028309/1[MRC] Medical Research Councilhttp://dx.doi.org/10.13039/501100000265

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