Power of the adjusted Q statistic to evaluate heterogeneity in meta-analyses of cluster randomized trials

Autor:	Allan Donner, Neil Klar, Shun Fu Lee
Rok vydání:	2017
Předmět:	Statistics and Probability Word error rate law.invention Nominal level Randomized controlled trial law Modeling and Simulation Meta-analysis Statistics Q-statistic Econometrics Cluster randomised controlled trial Statistic Type I and type II errors Mathematics
Zdroj:	Communications in Statistics - Simulation and Computation. 46:7062-7073
ISSN:	1532-4141 0361-0918
DOI:	10.1080/03610918.2016.1222426
Popis:	1. AbstractBecause of its simplicity, the Q statistic is frequently used to test the heterogeneity of the estimated intervention effect in meta-analyses of individually randomized trials. However, it is inappropriate to apply it directly to the meta-analyses of cluster randomized trials without taking clustering effects into account. We consider the properties of the adjusted Q statistic for testing heterogeneity in the meta-analyses of cluster randomized trials with binary outcomes. We also derive an analytic expression for the power of this statistic to detect heterogeneity in meta-analyses, which can be useful when planning a meta-analysis. A simulation study is used to assess the performance of the adjusted Q statistic, in terms of its Type I error rate and power. The simulation results are compared to that obtained from the proposed formula. It is found that the adjusted Q statistic has a Type I error rate close to the nominal level of 5%, as compared to the unadjusted Q statistic commonly used to te...
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::ac3aaa74e31dbb129795a0d0aaa5b8a5 https://doi.org/10.1080/03610918.2016.1222426 Zobrazit plný text záznamu