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A basic introduction to fixedeffect and randomeffects ...
Research ArticleReceived 1 December 2009,Revised 19 August 2010,Accepted 25 August 2010 Published online in Wiley Online Library( ) DOI: basic introduction to fixed-effect andrandom-effects models for meta-analysisMichael Borensteina , Larry V. Hedgesb, Julian Higginscand Hannah R. RothsteindThere are two popular statistical models for meta-analysis, the fixed-effect model and the random-effects model. Thefact that these two models employ similar sets of formulas to compute statistics, and sometimes yield similar estimatesfor the various parameters, may lead people to believe that the models are interchangeable. In fact, though, the modelsrepresent fundamentally different assumptions about the data. The selection of the appropriate model is important toensure that the various statistics are estimated correctly. Additionally, and more fundamentally, the model serves toplace the analysis in context. It provides a framework for the goals of the analysis as well as for the interpretation ofthe this paper we explain the key assumptions of each model, and then outline the differences between the conclude with a discussion of factors to consider when choosing between the two models.
For illustrative purposes, we use fictional scenarios in which the goal is to estimate the mean score on a science aptitude test. This example is a bit unusual, in that the effect size is a simple mean, whereas most meta-analyses employ an effect size that ... 97. M. BORENSTEIN ET AL. Figure 1. Example of a fixed-effect analysis. Figure 2 ...
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