title: Random-effects model for meta-analysis of clinical trials: an update.
abstract: The random-effects model is often used for meta-analysis of clinical studies. The method explicitly accounts for the heterogeneity of studies through a statistical parameter representing the inter-study variation. We discuss several iterative and non-iterative alternative methods for estimating the inter-study variance and hence the overall population treatment effect. We show that the leading methods for estimating the inter-study variance are special cases of a general method-of-moments estimate of the inter-study variance. The general method suggests two new two-step methods. The iterative estimate is statistically optimal and it can be easily calculated on a spreadsheet program, such as Microsoft Excel, available on the desktop of most researchers. The two-step methods approximate the optimal iterative method better than the earlier one-step non-iterative methods.
authors.affiliation: Biostatistics Research Branch, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, Bethesda, Maryland, USA. DerSimonian@nih.gov
authors.forename: Rebecca
authors.initials: R
authors.lastname: DerSimonian
authors.forename: Raghu
authors.initials: R
authors.lastname: Kacker
mesh_terms: D000465:Algorithms; D000704:Analysis of Variance; D002986:Clinical Trials as Topic; D003198:Computer Simulation; D006801:Humans; D015201:Meta-Analysis as Topic; D015233:Models, Statistical; D012107:Research Design