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An accurate test for homogeneity of odds ratios based on Cochran’s Q-statistic

BACKGROUND: A frequently used statistic for testing homogeneity in a meta-analysis of K independent studies is Cochran’s Q. For a standard test of homogeneity the Q statistic is referred to a chi-square distribution with K−1 degrees of freedom. For the situation in which the effects of the studies a...

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Detalles Bibliográficos
Autores principales: Kulinskaya, Elena, Dollinger, Michael B
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4531442/
https://www.ncbi.nlm.nih.gov/pubmed/26054650
http://dx.doi.org/10.1186/s12874-015-0034-x
Descripción
Sumario:BACKGROUND: A frequently used statistic for testing homogeneity in a meta-analysis of K independent studies is Cochran’s Q. For a standard test of homogeneity the Q statistic is referred to a chi-square distribution with K−1 degrees of freedom. For the situation in which the effects of the studies are logarithms of odds ratios, the chi-square distribution is much too conservative for moderate size studies, although it may be asymptotically correct as the individual studies become large. METHODS: Using a mixture of theoretical results and simulations, we provide formulas to estimate the shape and scale parameters of a gamma distribution to fit the distribution of Q. RESULTS: Simulation studies show that the gamma distribution is a good approximation to the distribution for Q. CONCLUSIONS: Use of the gamma distribution instead of the chi-square distribution for Q should eliminate inaccurate inferences in assessing homogeneity in a meta-analysis. (A computer program for implementing this test is provided.) This hypothesis test is competitive with the Breslow-Day test both in accuracy of level and in power. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12874-015-0034-x) contains supplementary material, which is available to authorized users.