The random-effects model is a useful approach for meta-analysis of clinical studies. It 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 are useful when a non-iterative estimate is desired.
Citation: Controlled Clinical Trials
Pub Type: Journals
clinical trials, meta-analysis, random effects model, restricted maximum likelihood, variance components