Estimation in meta-analyses of mean difference and standardized mean difference

Bakbergenuly, Ilyas, Hoaglin, David and Kulinskaya, Elena (2020) Estimation in meta-analyses of mean difference and standardized mean difference. Statistics in Medicine, 39 (2). pp. 171-191. ISSN 0277-6715

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Abstract

Methods for random-effects meta-analysis require an estimate of the between-study variance, τ 2. The performance of estimators of τ 2 (measured by bias and coverage) affects their usefulness in assessing heterogeneity of study-level effects and also the performance of related estimators of the overall effect. However, as we show, the performance of the methods varies widely among effect measures. For the effect measures mean difference (MD) and standardized MD (SMD), we use improved effect-measure-specific approximations to the expected value of Q for both MD and SMD to introduce two new methods of point estimation of τ 2 for MD (Welch-type and corrected DerSimonian-Laird) and one WT interval method. We also introduce one point estimator and one interval estimator for τ 2 in SMD. Extensive simulations compare our methods with four point estimators of τ 2 (the popular methods of DerSimonian-Laird, restricted maximum likelihood, and Mandel and Paule, and the less-familiar method of Jackson) and four interval estimators for τ 2 (profile likelihood, Q-profile, Biggerstaff and Jackson, and Jackson). We also study related point and interval estimators of the overall effect, including an estimator whose weights use only study-level sample sizes. We provide measure-specific recommendations from our comprehensive simulation study and discuss an example.

Item Type:	Article
Additional Information:	© 2019 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.
Uncontrolled Keywords:	between-study variance,random-effects model,meta-analysis,mean difference,standardized mean difference
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Medicine and Health Sciences > Research Centres > Business and Local Government Data Research Centre (former - to 2023) Faculty of Science > Research Groups > Data Science and Statistics Faculty of Science > Research Groups > Norwich Epidemiology Centre Faculty of Medicine and Health Sciences > Research Groups > Norwich Epidemiology Centre
Related URLs:	http://www.scopus.com/inward/record.url?...
Depositing User:	LivePure Connector
Date Deposited:	06 Nov 2019 09:30
Last Modified:	21 Apr 2023 00:12
URI:	https://ueaeprints.uea.ac.uk/id/eprint/72882
DOI:	10.1002/sim.8422

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