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Activity Number:
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427
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Type:
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Contributed
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Date/Time:
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Wednesday, August 9, 2006 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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| Abstract - #307308 |
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Title:
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Comparative Validity and Power of Methods for Association-Testing with Related Individuals
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Author(s):
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Hemant Tiwari*+ and Amit Patki and Mark Beasley and David B. Allison
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Companies:
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The University of Alabama at Birmingham and The University of Alabama at Birmingham and The University of Alabama at Birmingham and The University of Alabama at Birmingham
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Address:
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1665 University Blvd., Birmingham, AL, 35294,
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Keywords:
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association ; within-cluster resampling ; power ; type 1 error ; assoc ; FBAT
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Abstract:
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Hoffman et el. (2001) proposed an elegant resampling method for analyzing clustered binary data. The focus of their paper was to perform association tests on clustered binary data using within-cluster-resampling (WCR) method. WCR can be easily extended to continuous data and is a computationally intensive but simple and highly flexible method. Considering family as a cluster, one can apply WCR to familial data. In this presentation, we compare WCR with other existing methods of association for familial data such as the maximum-likelihood-based (George & Elston, 1987) and the family-based association test (FBAT) (Laired et al, 2001). We evaluated these methods' performance based on type 1 error rates and power of the study for given genetic parameters using simulation. WCR outperformed all other methods with respect to both type 1 error rates & power in all scenarios considered.
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