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According to Davey et al. (2011) with a total of 22,453 meta-analyses fromthe January 2008 Issue of the Cochrane Database of Systematic Reviews, themedian number of studies included in each meta-analysis is only three. In otherwords, about a half or more of meta-analyses conducted in the literatureinclude only two or three studies. While the common-effect model (also referredto as the fixed-effect model) may lead to misleading results when theheterogeneity among studies is large, the conclusions based on therandom-effects model may also be unreliable when the number of studies issmall. Alternatively, the fixed-effects model avoids the restrictive assumptionin the common-effect model and the need to estimate the between-study variancein the random-effects model. We note, however, that the fixed-effects model isunder appreciated and rarely used in practice until recently. In this paper, wecompare all three models and demonstrate the usefulness of the fixed-effectsmodel when the number of studies is small. In addition, we propose a newestimator for the unweighted average effect in the fixed-effects model.Simulations and real examples are also used to illustrate the benefits of thefixed-effects model and the new estimator.

Fixed-effects model: the most convincing model for meta-analysis with few studies