A re‐evaluation of the ‘quantile approximation method’ for random effects meta‐analysis |
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Authors: | Dan Jackson Jack Bowden |
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Affiliation: | MRC Biostatistics Unit, Institute of Public Health, Robinson Way, Cambridge CB2 2SR, U.K. |
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Abstract: | The quantile approximation method has recently been proposed as a simple method for deriving confidence intervals for the treatment effect in a random effects meta‐analysis. Although easily implemented, the quantiles used to construct intervals are derived from a single simulation study. Here it is shown that altering the study parameters, and in particular introducing changes to the distribution of the within‐study variances, can have a dramatic impact on the resulting quantiles. This is further illustrated analytically by examining the scenario where all trials are assumed to be the same size. A more cautious approach is therefore suggested, where the conventional standard normal quantile is used in the primary analysis, but where the use of alternative quantiles is also considered in a sensitivity analysis. Copyright © 2008 John Wiley & Sons, Ltd. |
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Keywords: | meta‐analysis random effects model quantile approximation method |
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