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Abstract Details
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Activity Number:
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659
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Type:
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Contributed
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Date/Time:
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Thursday, August 4, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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| Abstract - #303374 |
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Title:
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A U-Statistic-Based Random Forest Approach for Longitudinal Markers
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Author(s):
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Chengcheng Hu*+ and Victor De Gruttola
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Companies:
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University of Arizona and Harvard School of Public Health
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Address:
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1295 N Martin Ave, Tucson, AZ, 85724,
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Keywords:
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longitudinal data ;
random forest ;
recursive partitioning ;
haplotype ;
HIV ;
immune reconstitution
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Abstract:
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We develop a random forest approach to correlate unobserved haplotypes with trajectory of repeatedly measured outcomes. The splitting criterion used for tree construction in such a forest is based on a class of U-type score statistics. This method is nonparametric in nature, and can be used to study longitudinal outcomes which are difficult to analyze using parametric models. The proposed method is then applied to data from a candidate gene study on immune reconstitution of HIV-infected subjects.
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Authors who are presenting talks have a * after their name.
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