A modified random-effect procedure for combining risk difference in sets of 2×2 tables from clinical trials |
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Authors: | John D Emerson David C Hoaglin Frederick Mosteller |
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Institution: | (1) Middlebury College, U.S.A.;(2) Department of Statistics, Harvard University, 1, Oxford Street, 02138 Cambridge, Massachusetts, U.S.A. |
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Abstract: | Summary Meta-analyses of sets of clinical trials often combine risk differences from several 2×2 tables according to a random-effects
model. The DerSimonian-Laird random-effects procedure, widely used for estimating the populaton mean risk difference, weights
the risk difference from each primary study inversely proportional to an estimate of its variance (the sum of the between-study
variance and the conditional within-study variance). Because those weights are not independent of the risk differences, however,
the procedure sometimes exhibits bias and unnatural behavior. The present paper proposes a modified weighting scheme that
uses the unconditional within-study variance to avoid this source of bias. The modified procedure has variance closer to that
available from weighting by ideal weights when such weights are known. We studied the modified procedure in extensive simulation
experiments using situations whose parameters resemble those of actual studies in medical research. For comparison we also
included two unbiased procedures, the unweighted mean and a sample-size-weighted mean; their relative variability depends
on the extent of heterogeneity among the primary studies. An example illustrates the application of the procedures to actual
data and the differences among the results.
This research was supported by Grant HS 05936 from the Agency for Health Care Policy and Research to Harvard University. |
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Keywords: | Clinical trials DerSimonian-Laird method Meta-analysis Random effects Risk difference Semiweighted mean 2×2 tables Weighted mean |
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