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Activity Number: 440
Type: Contributed
Date/Time: Wednesday, August 5, 2009 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics in Epidemiology
Abstract - #303428
Title: Quantitative Synthesis of Dichotomous Data: Avoiding Dominance of a Single Study
Author(s): Kepher H. Makambi*+
Companies: Georgetown University Medical Center
Address: Lombardi Comprehensive Cancer Center, Washington, DC, 20057,
Keywords: random effects model ; truncated heterogeneity variance estimator ; weighted mean ; bias ; mean square error
Abstract:

Weighting of studies in meta-analysis is usually implemented using the estimated inverse variances of treatment effect estimates. In some situations,however, there is a likelihood of one study dominating other studies in the estimation process by taking on a normalized weight that is above some upper limit (Cochran, 1937, 1954). We implement an estimator of the heterogeneity variance that takes advantage of dominance adjusted weights. The performance of this estimator is compared with that of the commonly used estimator in meta-analysis, the DerSimonian-Laird estimator. A test procedure for the overall treatment effect is proposed that emanates from the quadratic form associated with the proposed heterogeneity variance estimator. An example is given to illustrate the application of these procedures.

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