Random-effects model for meta-analysis of clinical trials: an update.

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.

[1]  N. Laird,et al.  Meta-analysis in clinical trials. , 1986, Controlled clinical trials.

[2]  John Mandel,et al.  Consensus Values and Weighting Factors. , 1982, Journal of research of the National Bureau of Standards.

[3]  R Peto,et al.  Effects of intravenous magnesium in suspected acute myocardial infarction: overview of randomised trials. , 1991, BMJ.

[4]  C D Naylor,et al.  Meta-analysis of controlled clinical trials. , 1989, The Journal of rheumatology.

[5]  Andrew L. Rukhin,et al.  Restricted maximum likelihood estimation of a common mean and the Mandel–Paule algorithm , 2000 .

[6]  R. N. Kackar,et al.  Approximations for Standard Errors of Estimators of Fixed and Random Effects in Mixed Linear Models , 1984 .

[7]  R. Peto,et al.  Beta blockade during and after myocardial infarction: an overview of the randomized trials. , 1985, Progress in cardiovascular diseases.

[8]  R. Dersimonian,et al.  Resolving discrepancies between a meta-analysis and a subsequent large controlled trial. , 1999, JAMA.

[9]  Sonia S Anand,et al.  Oral anticoagulant therapy in patients with coronary artery disease: a meta-analysis. , 1999, JAMA.

[10]  D. Harville Maximum Likelihood Approaches to Variance Component Estimation and to Related Problems , 1977 .

[11]  Chukiat Viwatwongkasem,et al.  Some general points in estimating heterogeneity variance with the DerSimonian-Laird estimator. , 2002, Biostatistics.

[12]  J. Bruix,et al.  Systematic review of randomized trials for unresectable hepatocellular carcinoma: Chemoembolization improves survival , 2003, Hepatology.

[13]  W. G. Cochran The combination of estimates from different experiments. , 1954 .

[14]  Raghu N. Kacker,et al.  Combining information from interlaboratory evaluations using a random effects model , 2004 .

[15]  S. Goodman,et al.  Cardiac resynchronization and death from progressive heart failure: a meta-analysis of randomized controlled trials. , 2003, JAMA.

[16]  T. Chalmers,et al.  A survey of clinical trials of antibiotic prophylaxis in colon surgery: evidence against further use of no-treatment controls. , 1981, The New England journal of medicine.

[17]  Jeffrey R. Wilson,et al.  CLASP: a randomised trial of low-dose aspirin for the prevention and treatment of pre-eclampsia among 9364 pregnant women , 1994, The Lancet.