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Assessing Heterogeneity in Meta-Analysis: Q Statistic or I2 Index?

Assessing Heterogeneity in Meta-Analysis: Q Statistic or I2 Index? In meta-analysis, the usual way of assessing whether a set of single studies is homogeneous is by means of the Q test. However, the Q test only informs meta-analysts about the presence versus the absence of heterogeneity, but it does not report on the extent of such heterogeneity. Recently, the I2 index has been proposed to quantify the degree of heterogeneity in a meta-analysis. In this article, the performances of the Q test and the confidence interval around the I2 index are compared by means of a Monte Carlo simulation. The results show the utility of the I2 index as a complement to the Q test, although it has the same problems of power with a small number of studies. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Psychological Methods American Psychological Association

Assessing Heterogeneity in Meta-Analysis: Q Statistic or I2 Index?

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References (64)

Publisher
American Psychological Association
Copyright
Copyright © 2006 American Psychological Association
ISSN
1082-989x
eISSN
1939-1463
DOI
10.1037/1082-989X.11.2.193
pmid
16784338
Publisher site
See Article on Publisher Site

Abstract

In meta-analysis, the usual way of assessing whether a set of single studies is homogeneous is by means of the Q test. However, the Q test only informs meta-analysts about the presence versus the absence of heterogeneity, but it does not report on the extent of such heterogeneity. Recently, the I2 index has been proposed to quantify the degree of heterogeneity in a meta-analysis. In this article, the performances of the Q test and the confidence interval around the I2 index are compared by means of a Monte Carlo simulation. The results show the utility of the I2 index as a complement to the Q test, although it has the same problems of power with a small number of studies.

Journal

Psychological MethodsAmerican Psychological Association

Published: Jun 1, 2006

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