Investigating mood regulation and smoking: Applications of mixed-effects location-scale models for intensive longitudinal data
Donald Hedeker, Ph.D.
University of Chicago
Ecological momentary assessment and/or experience sampling methods are increasingly used in health and psychological studies to study subjective experiences within changing environmental contexts. In these studies, up to 30 or 40 observations are often obtained for each subject, and so these data are also called intensive longitudinal data. Because there are so many measurements per subject, one can characterize a subject’s mean and variance and can specify models for both. In this presentation, we focus on an adolescent smoking study using ecological momentary assessment where interest is on characterizing changes in mood variation associated with smoking. We describe how covariates can influence the mood variances and also extend the statistical model by adding a subject-level random effect to the within-subject variance specification. This permits subjects to have influence on the mean, or location, and variability, or (square of the) scale, of their mood responses. These mixed-effects location scale models have useful applications in many research areas where interest centers on the joint modeling of the mean and variance structure