You are not logged in.

Finding the power to reduce publication bias

Stanley, TD, Doucouliagos, Chris and Ioannidis, JPA 2017, Finding the power to reduce publication bias, Statistics in medicine, vol. 35, pp. 1580-1598, doi: 10.1002/sim.7228.

Attached Files
Name Description MIMEType Size Downloads

Title Finding the power to reduce publication bias
Author(s) Stanley, TD
Doucouliagos, ChrisORCID iD for Doucouliagos, Chris
Ioannidis, JPA
Journal name Statistics in medicine
Volume number 35
Start page 1580
End page 1598
Total pages 19
Publisher Wiley
Place of publication London, Eng.
Publication date 2017
ISSN 0277-6715
Summary The central purpose of this study is to document how a sharper focus upon statistical power may reduce the impact of selective reporting bias in meta-analyses. We introduce the weighted average of the adequately powered (WAAP) as an alternative to the conventional random-effects (RE) estimator. When the results of some of the studies have been selected to be positive and statistically significant (i.e. selective reporting), our simulations show that WAAP will have smaller bias than RE at no loss to its other statistical properties. When there is no selective reporting, the difference between RE's and WAAP's statistical properties is practically negligible. Nonetheless, when selective reporting is especially severe or heterogeneity is very large, notable bias can remain in all weighted averages. The main limitation of this approach is that the majority of meta-analyses of medical research do not contain any studies with adequate power (i.e. >80%). For such areas of medical research, it remains important to document their low power, and, as we demonstrate, an alternative unrestricted weighted least squares weighted average can be used instead of WAAP.
Language eng
DOI 10.1002/sim.7228
Field of Research 0104 Statistics
1117 Public Health And Health Services
Socio Economic Objective 970114 Expanding Knowledge in Economics
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2017, John Wiley & Sons, Ltd.
Persistent URL

Document type: Journal Article
Collection: Department of Economics
Connect to link resolver
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 2 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 22 Abstract Views, 3 File Downloads  -  Detailed Statistics
Created: Thu, 23 Feb 2017, 07:55:55 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact