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A re-evaluation of the ‘quantile approximation method’ for random effects meta-analysis

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...

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Detalles Bibliográficos
Autores principales: Jackson, Dan, Bowden, Jack
Formato: Texto
Lenguaje:English
Publicado: John Wiley & Sons, Ltd. 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2991773/
https://www.ncbi.nlm.nih.gov/pubmed/19016302
http://dx.doi.org/10.1002/sim.3487
Descripción
Sumario: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.