Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/30325
Title: | Modified power prior with multiple historical trials for binary endpoints | Authors: | TEREDA, Akalu Van Rosmalen, Joost Dejardin, David LESAFFRE, Emmanuel |
Issue Date: | 2019 | Publisher: | Wiley | Source: | Statistics in Medicine, 38 (7) , p. 1147 -1169 | Abstract: | Including historical data may increase the power of the analysis of a current clinical trial and reduce the sample size of the study. Recently, several Bayesian methods for incorporating historical data have been proposed. One of the methods consists of specifying a so-called power prior whereby the historical likelihood is downweighted with a weight parameter. When the weight parameter is also estimated from the data, the modified power prior (MPP) is needed. This method has been used primarily when a single historical trial is available. We have adapted the MPP for incorporating multiple historical control arms into a current clinical trial, each with a separate weight parameter. Three priors for the weights are considered: (1) independent, (2) dependent, and (3) robustified dependent. The latter is developed to account for the possibility of a conflict between the historical data and the current data. We analyze two real-life data sets and perform simulation studies to compare the performance of competing Bayesian methods that allow to incorporate historical control patients in the analysis of a current trial. The dependent power prior borrows more information from comparable historical studies and thereby can improve the statistical power. Robustifying the dependent power prior seems to protect against prior-data conflict. | Keywords: | Bayesian inference;dependent weights;modified power prior;multiple historical trials | Document URI: | http://hdl.handle.net/1942/30325 | ISSN: | 0277-6715 | e-ISSN: | 1097-0258 | DOI: | 10.1002/sim.8019 | ISI #: | WOS:000460306500004 | Rights: | 2018 John Wiley & Sons, Ltd. | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2020 |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Banbeta_et_al-2019-Statistics_in_Medicine.pdf Restricted Access | Published version | 949.61 kB | Adobe PDF | View/Open Request a copy |
Peer_reviewed_version.pdf | Peer-reviewed author version | 372.13 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.