Document Type

Article

Publication Date

Spring 3-1-2015

Publication Title

Research Synthesis Methods

Volume

6

Issue

1

Pages

63-73

Abstract

Meta-analysis multiplicity, the concept of conducting multiple tests of statistical significance within one study, is an underdeveloped literature (Tendal, Nüesch, Higgins, Jüni, & Gøtzsche, 2011). We address this issue by considering how Type I errors can impact meta-analytic results, suggest how statistical power may be affected through the use of multiplicity corrections, and propose how meta-analysts should analyze multiple tests of statistical significance. The context for this study is a meta-review of meta-analyses published in two leading review journals in education and psychology. Our review of 130 meta-analyses revealed a strong reliance on statistical significance testing without considering of Type I errors or the use of multiplicity corrections. In order to provide valid conclusions, meta-analysts must consider these issues prior to conducting the study.

Comments

Author Posting. © 2014 John Wiley & Sons, Ltd. This is the author's version of the work. It is posted here by permission of Wiley for personal use, not for redistribution. The definitive version was published in Research Synthesis Methods Volume 6, Issue 1, pages 63–73, March 2015. http://dx.doi.org/10.1002/jrsm.1124

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.

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