title: Mixed effects models for recurrent events data with partially observed time-varying covariates: Ecological momentary assessment of smoking.
abstract: Cigarette smoking is a prototypical example of a recurrent event. The pattern of recurrent smoking events may depend on time-varying covariates including mood and environmental variables. Fixed effects and frailty models for recurrent events data assume that smokers have a common association with time-varying covariates. We develop a mixed effects version of a recurrent events model that may be used to describe variation among smokers in how they respond to those covariates, potentially leading to the development of individual-based smoking cessation therapies. Our method extends the modified EM algorithm of Steele (1996) for generalized mixed models to recurrent events data with partially observed time-varying covariates. It is offered as an alternative to the method of Rizopoulos, Verbeke, and Lesaffre (2009) who extended Steele's (1996) algorithm to a joint-model for the recurrent events data and time-varying covariates. Our approach does not require a model for the time-varying covariates, but instead assumes that the time-varying covariates are sampled according to a Poisson point process with known intensity. Our methods are well suited to data collected using Ecological Momentary Assessment (EMA), a method of data collection widely used in the behavioral sciences to collect data on emotional state and recurrent events in the every-day environments of study subjects using electronic devices such as Personal Digital Assistants (PDA) or smart phones.
authors.affiliation: Department of Epidemiology and Biostatistics, University of Georgia, Athens, Georiga, U.S.A.
authors.forename: Stephen L
authors.initials: SL
authors.lastname: Rathbun
authors.affiliation: Department of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania, U.S.A.
authors.forename: Saul
authors.initials: S
authors.lastname: Shiffman
mesh_terms: D000339:Affect; D003198:Computer Simulation; D006801:Humans; D015994:Incidence; D015233:Models, Statistical; D009042:Motivation; D011594:Psychometrics / Q000379:methods*; D012008:Recurrence; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012907:Smoking / Q000453:epidemiology / Q000523:psychology*; D016540:Smoking Cessation / Q000523:psychology* / Q000706:statistics & numerical data*; D000074606:Smoking Prevention; D012931:Social Environment
keywords: Fully exponential Laplace approximation; Modified EM algorithm; Probability sample; Random covariate effects