Maximum-likelihood methods for meta-analysis: A tutorial using R. (May 2015)

• Record Type: Journal Article
• Authors: Vevea, Jack L.; Coburn, Kathleen M.
• Other Names: Gaertner Lowell guest-editor.; Packer Dominic guest-editor.
• Is Part Of: Group processes and intergroup relations. Volume 18:Number 3(2015:May)
• Page Start: 329
• Page End: 347
• Publication Date: 2015-05
• Subjects: maximum likelihood -- meta-analysis -- mixed effects -- open source -- random effects; Intergroup relations -- Periodicals; Social groups -- Periodicals; 302.305
• DOI: 10.1177/1368430214558311
• Languages: English
• ISSNs: 1368-4302

Abstract

The method of maximum likelihood provides a versatile way to estimate and conduct inference about moderators of effect size in meta-analytic models. The metafor package for the open-source statistical software R offers easy access to this method. We discuss inferential choices that the meta-analyst must make, and advocate the general choice of random-effects methods. We demonstrate the use of the metafor package using data from two meta-analyses that address group processes. These demonstrations illustrate two contrasting approaches to meta-analytic inference: a priori random-effects inference and conditionally random inference. The examples show that these approaches typically lead to the same conclusions when applied correctly.