Joint modeling of longitudinal and time-to-event data in NLST
Principal Investigator
Name
Fenghai Duan
Degrees
PhD
Institution
Brown University
Position Title
Biotatistician
Email
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
201111-0041
Initial CDAS Request Approval
Nov 29, 2011
Title
Joint modeling of longitudinal and time-to-event data in NLST
Summary
Currently, these two outcomes are mainly analyzed separately, e.g., fitting a mixed effects model for the longitudinal data and fitting a Cox proportional hazards model for survival outcome. However, these approaches do not consider the dependency between them. There are situations that a joint modeling is of more interest and more appropriate, e.g., analyzing the time-to-event outcome while taking account of the dependency and association between the longitudinal measures and the time-to-event data (i.e., conducting survival analysis with a time-dependent covariate) (Diggle et al, 2008; Brown 2009). The research in this area started in the late 90s and has been boosted in the last decade (Hogan and Laird 1997; Henderson et al. 2000; Xu and Zeger 2001; Song et al 2002; Chi et al 2006; Cai et al. 2006; Diggle et al 2008; Williamson et al 2008; Brown 2009; Subtil et al 2009; Ibrahim et al 2010). There are two excellent review articles given by Tsiatis and Davidian (2004), and Ibrahim et al (2010).
Collaborators
Constantine Gatsonis
Richard Fagerstrom
Timothy Church