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Abstract Details
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Activity Number:
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359
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Type:
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Contributed
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Date/Time:
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Tuesday, August 2, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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| Abstract - #300615 |
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Title:
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Multivariate Random Effects Meta-Analysis: An Extension
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Author(s):
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Kepher H. Makambi*+ and Hyunuk Seung
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Companies:
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Georgetown University and Georgetown University
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Address:
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3800 Reservoir Road, NW, Washington, DC, 20057,
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Keywords:
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Heterogeneity variance estimator ;
overall treatment effect ;
bias
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Abstract:
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In univariate and multivariate meta-analysis, a number of iterative and non-iterative approaches exist including the DerSimonian and Laird (D-L), maximum likelihood (ML) and restricted maximum likelihood methods (REML). Based on procedures developed by Hartung and Makambi (2002), we propose a simple multivariate extension along the lines of Jackson et al. (2009). A comparison of the bias with the multivariate DerSimonian-Laird approach through simulations indicates that our approach is competitive. An example is presented to demonstrate the application of our approach.
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