Meta-analysis of effect sizes reported at multiple time points using general linear mixed model

Show simple item record Musekiwa, Alfred Manda, S.O.M. (Samuel) Mwambi, Henry G. Chen, Ding-Geng (Din) 2016-12-05T09:15:29Z 2016-12-05T09:15:29Z 2016-10-31
dc.description S1 Fig. R-code for meta-analysis. en_ZA
dc.description.abstract Meta-analysis of longitudinal studies combines effect sizes measured at pre-determined time points. The most common approach involves performing separate univariate metaanalyses at individual time points. This simplistic approach ignores dependence between longitudinal effect sizes, which might result in less precise parameter estimates. In this paper, we show how to conduct a meta-analysis of longitudinal effect sizes where we contrast different covariance structures for dependence between effect sizes, both within and between studies. We propose new combinations of covariance structures for the dependence between effect size and utilize a practical example involving meta-analysis of 17 trials comparing postoperative treatments for a type of cancer, where survival is measured at 6, 12, 18 and 24 months post randomization. Although the results from this particular data set show the benefit of accounting for within-study serial correlation between effect sizes, simulations are required to confirm these results. en_ZA
dc.description.department Statistics en_ZA
dc.description.librarian am2016 en_ZA
dc.description.uri en_ZA
dc.identifier.citation Musekiwa A, Manda SOM, Mwambi HG, Chen D-G (2016) Meta-Analysis of Effect Sizes Reported at Multiple Time Points Using General Linear Mixed Model. PLoS ONE 11(10): e0164898. DOI: 10.1371/journal.pone.0164898. en_ZA
dc.identifier.issn 1932-6203
dc.identifier.other 10.1371/journal.pone.0164898
dc.language.iso en en_ZA
dc.publisher Public Library of Science en_ZA
dc.rights © 2016 Musekiwa et al. This is an open access article distributed under the terms of the Creative Commons Attribution License. en_ZA
dc.subject Meta-analysis en_ZA
dc.subject Longitudinal effect sizes en_ZA
dc.subject Covariance structures for dependence en_ZA
dc.subject Effect sizes en_ZA
dc.subject Multiple time points en_ZA
dc.subject General linear mixed model en_ZA
dc.title Meta-analysis of effect sizes reported at multiple time points using general linear mixed model en_ZA
dc.type Article en_ZA

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