2020/02/11 by Enxuan Lin, Lin, Enxuan, Tiejun Tong +5 · 1 citation
Decision Sciences · Mathematics · #FOS: Computer and information sciences #Meta-analysis and systematic reviews #Methodology (stat.ME) #Statistical Methods in Clinical Trials
paper · pdf · doi:10.48550/arxiv.2002.04211
openalex publication_date 2020/02/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
According to Davey et al. (2011) with a total of 22,453 meta-analyses from the January 2008 Issue of the Cochrane Database of Systematic Reviews, the median number of studies included in each meta-analysis is only three. In other words, about a half or more of meta-analyses conducted in the literature include only two or three studies. While the common-effect model (also referred to as the fixed-effect model) may lead to misleading results when the heterogeneity among studies is large, the conclusions based on the random-effects model may also be unreliable when the number of studies is small. Alternatively, the fixed-effects model avoids the restrictive assumption in the common-effect model and the need to estimate the between-study variance in the random-effects model. We note, however, that the fixed-effects model is under appreciated and rarely used in practice until recently. In this paper, we compare all three models and demonstrate the usefulness of the fixed-effects model when the number of studies is small. In addition, we propose a new estimator for the unweighted average effect in the fixed-effects model. Simulations and real examples are also used to illustrate the benefits of the fixed-effects model and the new estimator.