TIME-VARYING COEFFICIENT MODELS FOR JOINT MODELING BINARY AND CONTINUOUS OUTCOMES IN LONGITUDINAL DATA.

ABSTRACT: Motivated by an empirical analysis of ecological momentary assessment data (EMA) collected in a smoking cessation study, we propose a joint modeling technique for estimating the time-varying association between two intensively measured longitudinal responses: a continuous one and a binary one. A major challenge in joint modeling these responses is the lack of a multivariate distribution. We suggest introducing a normal latent variable underlying the binary response and factorizing the model into two components: a marginal model for the continuous response, and a conditional model for the binary response given the continuous response. We develop a two-stage estimation procedure and establish the asymptotic normality of the resulting estimators. We also derived the standard error formulas fo

SUBMITTER: Kurum E 

PROVIDER: S-EPMC5033066 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature