Random-Effects Model for Meta-analysis of Clinical Trials: An Update
Rebecca DerSimonian, Raghu N. Kacker
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.
and Kacker, R.
Random-Effects Model for Meta-analysis of Clinical Trials: An Update, Controlled Clinical Trials, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=51313
(Accessed May 28, 2023)