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Activity Number: 236
Type: Topic Contributed
Date/Time: Monday, August 10, 2015 : 2:00 PM to 3:50 PM
Sponsor: SSC
Abstract #316239 View Presentation
Title: The Statistical Applications of Functional Data Analysis in Physical Activity Studies
Author(s): Tyler Williamson* and Haocheng Li and John Staudenmayer and Sarah Kozey-Keadle and Raymond Carroll
Companies: University of Calgary and University of Calgary and University of Massachusetts and National Cancer Institute and Texas A&M University
Keywords: functional data analysis ; physical activity ; high dimensional data ; multilevel modelling ; multivariate modelling

Research about the links between physical activity patterns and health outcomes has traditionally been based on fairly crude self-report instruments such as questionnaires. This field is being revolutionized by the availability of relatively cheap wearable accelerometer devices. These devices produce thousands of observations per person per day in some cases on a second by second basis, and depending on the device, can measure whether the person is asleep, lying down, sitting, standing, and, when a person is moving, produce data about the amount of energy expended by physical activity. Statistically, the problem can be cast as densely sampled high dimensional functional data with binary and continuous outcomes. We describe hierarchical multi-dimensional methods that exploit such functional data to show how lifestyle intervention can affect sedentary time, interruptions of sedentary behaviour and expenditure of energy from moderate to vigorous physical activity.

Authors who are presenting talks have a * after their name.

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