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Concurrent

Longitudinal Data & Wearable Technology

Thu, Oct 29, 10:00 AM - 11:30 AM

4 Abstracts

Predictive Modeling for Irregular and Unbalanced Longitudinal Data: Application to Bariatric Surgery Outcomes

Kristina Vatcheva (University of Texas Rio Grande Valley)

Co-authors: R. Armour Forse (DHR), Daniel Gutierrez III (UTRGV)

statistical methods machine learning deep learning bariatric surgery

Policy and life-event drivers of dynamic health-risk profiles in later life: A latent transition analysis of HRS

Co-authors: Nidhi Kohli (Department of Educational Psychology, University of Minnesota), Xiaojing Wang (University of Connecticut)

Latent transition analysis (LTA)Latent class analysis (LCA)Hidden Markov model Mixture modeling Longitudinal latent class modeling Self-rated health Health and Retirement Study (HRS)

Longitudinal UPDRS in Parkinson’s Telemonitoring: Comparing Multiple Imputation and Likelihood Based Mixed Models Under Missingness

Priscilla Kissi-Appiah

Longitudinal Data; Multiple Imputation; Mixed Models; Missing Data; Parkinson’s Disease; Telemonitoring

Innovative Imputation Strategies for Time Series Data from Wearable Devices and Mobile Applications

Qin Shao (University of Toledo)

missing data imputation time series wearables digital health Kalman filter state space models

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