This event is part of the Fall 2022 Interdisciplinary Seminar Series on Statistical Methodology for Social and Behavioral Research.
Shared Parameter Mixed-Effects Location Scale Models for Intensive Longitudinal Data
Presented by Dr. Donald Hedeker, University of Chicago
Friday, March 4
3 p.m. ET
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 an adolescent smoking study using EMA where interest is on characterizing changes in mood variation. 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. The random effects are then shared in a modeling of future smoking levels. 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.
Dr. Donald Hedeker’s chief expertise is in the development and use of advanced statistical methods for clustered and longitudinal data, with particular emphasis on mixed-effects models. He is the primary author of several freeware computer programs for mixed-effects analysis. With Robert Gibbons, Dr. Hedeker is the author of the text “Longitudinal Data Analysis,” published by Wiley in 2006. More recently, he has developed methods and software for analysis of intensive longitudinal data, which are data with many measurements over time, often collected using mobile devices and/or the internet. Such data are increasingly obtained by researchers in many research areas, for example in the areas of mobile health (mHealth) and ecological momentary assessment (EMA) studies. Dr. Hedeker is an associate editor for Statistics in Medicine, an elected member of the Society of Multivariate Experimental Psychology and the International Statistical Institute, and a Fellow of the American Statistical Association, receiving the Long-Term Excellence Award from ASA’s Health Policy Statistics Section in 2015. Dr. Hedeker earned his PhD in Quantitative Psychology and BA in Economics from the University of Chicago.