JSM 2011 Online Program

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Abstract Details

Activity Number: 597
Type: Invited
Date/Time: Thursday, August 4, 2011 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Computing
Abstract - #300399
Title: Functional Analysis for Clustered Actigraphy Data
Author(s): Jimin Ding*+ and Elena Deych and William Shannon and Tao Li and Jia Wang
Companies: Washington University at St. Louis and Washington University School of Medicine and Washington University School of Medicine and Washington University School of Medicine and Washington University School of Medicine
Address: One Brookings Dr., St. Louis, MO, 63130, USA
Keywords: Actigraphy Data ; Functional Data Analysis ; Functional Linear Mixed Effects Model
Abstract:

An actigraph is a watch-like device, usually attached to the wrist or leg, that contains accelerometers to measure movements in the form of activity counts every minute or every few seconds. As an emerging clinical technology, actigraphy data is often collected over several days for each participant to evaluate sleep, daytime activity, and circadian activity rhythms in people. In this talk, we view the measured activities of each day for each person as a function of time and analyze them using functional data analysis (FDA). The functional linear mixed effects model is applied to those clustered curves. Here, subject effects are captured through random effects while treatment effects are modeled through fixed effects. We employ principal components analysis for both within-subject and between-subject covariances to fit the model.


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