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Activity Number: 176 - Modeling
Type: Contributed
Date/Time: Monday, July 30, 2018 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Computing
Abstract #328553
Title: Dealing with Methodological Issues in the Functional Data Analysis of Actigraphy Data
Author(s): Stephen W. Looney* and William Vaughn McCall and Jordan S. Lundeen
Companies: Augusta University and Augusta University and BlueChoice HealthPlan of South Carolina
Keywords: basis functions; missing data; imputation; biomarker; validation; rest-activity data

This presentation examines several methodological issues we have encountered when using functional data analysis (FDA) to analyze actigraphy data. For example, we discuss and compare methods used for handling missing actigraphy data, and how to determine the optimal number of basis functions to use when applying FDA. Curves fit to actigraphy data must take on non-negative values, so we also discuss how to restrict FDA curves so that they have no negative values. The methods and issues we discuss are illustrated using actigraphy data from our study of the utility of a rest-activity biomarker to predict responsiveness to antidepressants.

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

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