Abstract #300370

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JSM 2002 Abstract #300370
Activity Number: 266
Type: Invited
Date/Time: Wednesday, August 14, 2002 : 8:30 AM to 10:20 AM
Sponsor: WNAR
Abstract - #300370
Title: Diagnostic Methods for Assessing Conditional Independence in Latent Variable Modelling of Joint Survival and Longitudinal Data
Author(s): Haiqun Lin*+
Affiliation(s): Yale University
Address: 60 College Street, P.O. Box 208034, New Haven, Connecticut, 06520-8034,
Keywords: joint analysis ; longitudinal ; survival ; conditional independence
Abstract:

In latent variable modeling of joint longitudinal and survival analysis, conditional independence, given the latent variables such as random effects or latent classes, is usually imposed between the longitudinal and event processes to facilitate modeling and inference. To assess this conditional independence assumption, we propose approaches where the dependence of the longitudinal process(es) on the event process as well as dependence of the event process on the observed realization of longitudinal process(es), are modeled, and the conditional independence model is nested within such dependence models. With sufficient number of latent variables and proper inclusion of covariate effects in the joint longitudinal and survival model, the conditional independence assumption is likely to be satisfied. We illustrate this method using two clinical data sets.

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