Joint modeling of survival time and longitudinal outcomes with flexible random effects.

TitleJoint modeling of survival time and longitudinal outcomes with flexible random effects.
Publication TypeJournal Article
Year of Publication2018
AuthorsChoi, Jaeun, Donglin Zeng, Andrew F. Olshan, and Jianwen Cai
JournalLifetime Data Anal
Volume24
Issue1
Pagination126-152
Date Published2018 01
ISSN1572-9249
KeywordsAlgorithms, Biometry, Computer Simulation, Head and Neck Neoplasms, Humans, Likelihood Functions, Linear Models, Longitudinal Studies, Normal Distribution, North Carolina, Proportional Hazards Models, Quality of Life, Survival Analysis
Abstract

Joint models with shared Gaussian random effects have been conventionally used in analysis of longitudinal outcome and survival endpoint in biomedical or public health research. However, misspecifying the normality assumption of random effects can lead to serious bias in parameter estimation and future prediction. In this paper, we study joint models of general longitudinal outcomes and survival endpoint but allow the underlying distribution of shared random effect to be completely unknown. For inference, we propose to use a mixture of Gaussian distributions as an approximation to this unknown distribution and adopt an Expectation-Maximization (EM) algorithm for computation. Either AIC and BIC criteria are adopted for selecting the number of mixtures. We demonstrate the proposed method via a number of simulation studies. We illustrate our approach with the data from the Carolina Head and Neck Cancer Study (CHANCE).

DOI10.1007/s10985-017-9405-4
Alternate JournalLifetime Data Anal
Original PublicationJoint modeling of survival time and longitudinal outcomes with flexible random effects.
PubMed ID28856493
PubMed Central IDPMC5756108
Grant ListP01 CA142538 / NH / NIH HHS / United States
R01 GM047845 / GM / NIGMS NIH HHS / United States
UL1 RR025747 / RR / NCRR NIH HHS / United States
P01 CA142538 / CA / NCI NIH HHS / United States
R01 ES021900 / ES / NIEHS NIH HHS / United States
P2C HD050924 / HD / NICHD NIH HHS / United States
R01 ES021900 / / National Institutes of Health (US) / International