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Activity Number: 341
Type: Topic Contributed
Date/Time: Tuesday, August 2, 2016 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract #320193
Title: Joint Modeling of Noncommensurate Sparse Functional Predictors with an Application to Ecological Momentary Assessment (EMA) Data
Author(s): Jaroslaw Harezlak* and Fei He and Armando Teixeira-Pinto
Companies: Indiana University Fairbanks School of Public Health and Indiana University Fairbanks School of Public Health and University of Sydney
Keywords: functional data ; non-commensurate outcomes ; ecological momentary assessment ; variable domain ; cross-dependence

We propose and evaluate models for bivariate functional data collected longitudinally. A number of extensions is entertained including cross-outcome effects, models for non-commensurate outcomes (e.g. continuous and binary), variable domains and a hierarchical dependence structure. Specifically, effects of functional predictors on non-commensurate bivariate outcomes are estimated taking into account correlations between the outcomes induced by the shared random effects. We apply the proposed methods to the ecological momentary assessment data studying the dependence of the relationship satisfaction and condom use amongst young adults participating in an STD study.

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

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