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Activity Number:
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64
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Type:
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Contributed
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Date/Time:
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Sunday, July 29, 2007 : 4:00 PM to 5:50 PM
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Sponsor:
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Biometrics Section
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| Abstract - #309048 |
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Title:
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Moving Block Bootstrap for Analyzing Longitudinal Data
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Author(s):
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Hyunsu Ju*+ and Suojin Wang
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Companies:
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The University of Texas Medical Branch and Texas A&M University
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Address:
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3.302 Jennie Sealy Hospital 301 University Blvd , Galveston, TX, 77550,
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Keywords:
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Longitudinal study ; Resampling methods ; Moving block bootstrap
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Abstract:
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Many longitudinal studies in which subjects are followed over time are the case that the number of subjects is large and the number of measurements per subject over time is small. We focus on a case where the number of replications over time is large relative to the number of subjects in the study. We investigate the use of moving block bootstrap methods involving resampling possibly overlapping blocks for analyzing such data rather than standard ordinary bootstrap or resampling subjects bootstrap. Asymptotic properties of the bootstrap methods in this setting are derived. The effectiveness of these block resampling methods is also demonstrated through a simulation study.
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