Two-stage mixed-effects location scale (MELS) models for intensive longitudinal data

Music City Center 

Intensive longitudinal data are increasingly encountered in many research areas. For example, ecological momentary assessment (EMA) and/or mobile health (mHealth) methods are often used to study subjective experiences within changing environmental contexts. In these studies, up to 30 or 40 observations are usually obtained for each subject over a period of a week or so, allowing one to characterize a subject's mean and variance and specify models for both. In this presentation, we focus on a smoking study of dual users (i.e., both combustible and electronic cigarette users) using EMA where interest is on characterizing changes in mood variation associated with these nicotine products, and whether subjects' mood response can predict future nicotine product use. At the first stage, the MELS model includes random subject effects for the mean (i.e., location), which characterize subjects' differential mood response to combustible and electronic cigarettes. A random effect for subjects' variability (i.e., scale) in mood responses is included to characterize subjects' mood consistency/erraticism. These random location and scale effects are used in a second stage regression, both linear and multinomial, model to predict future nicotine product use. Since the random effects are estimates, repeated draws from the posterior distribution of the random effects for each subject are utilized in the second stage model (i.e., plausible value replications), with results averaged across these repeated draws. A software program, MixWILD, which facilitates this two stage modeling approach, is described.

Ecological Momentary Assessment (EMA)

Experience Sampling Method

Variance modeling