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Random-Effects Model for Meta-analysis of Clinical Trials: An Update

Published

Author(s)

Rebecca DerSimonian, Raghu N. Kacker

Abstract

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
Volume
28

Keywords

clinical trials, meta-analysis, random effects model, restricted maximum likelihood, variance components

Citation

DerSimonian, R. and Kacker, R. (2007), 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 February 20, 2024)
Created December 31, 2006, Updated October 12, 2021