A Non-Iterative Extension of the Multivariate Random Effects Meta-Analysis
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https://tandf.figshare.com/articles/dataset/A_Non_Iterative_Extension_of_the_Multivariate_Random_Effects_Meta_Analysis/1029354/1
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资源简介：
<i>Multivariate methods in meta-analysis are becoming popular and more accepted in biomedical research despite computational issues in some of the techniques. A number of approaches, both iterative and non-iterative have been proposed including the multivariate DerSimonian and Laird method by Jackson et al. (2010), which is non-iterative. In this study, we propose an extension of the method by Hartung and Makambi (2002) and Makambi (2001) to multivariate situations. A comparison of the bias and mean square error from a simulation study indicates that, in some circumstances, the proposed approach perform better than the multivariate DerSimonian-Laird approach. An example is presented to demonstrate the application of the proposed approach.</i>
提供机构：
Taylor & Francis
创建时间：
2016-01-19
