Missing data approaches in longitudinal studies of aging: A case example using the National Health and Aging Trends Study.

Emilie D DuchesneauShahar ShmuelKeturah R FaurotAllison MustyJihye ParkTil StürmerAlan C KinlawYang Claire YangJennifer L Lund

Published in: PloS one (2023)

Missing data and loss-to-follow-up are common in longitudinal studies of aging. Robust epidemiologic methods can improve the rigor and interpretability of aging-related research.

Keyphrases

electronic health record
machine learning
deep learning
artificial intelligence