Degree Name
MS (Master of Science)
Program
Mathematical Sciences
Date of Award
8-2026
Committee Chair or Co-Chairs
Maryam Skafyan
Committee Members
Mostafa Zahed, Robert M Price
Abstract
Ecological Momentary Assessment is a method of collecting repeated measures of people in real time within natural environments. This results in hierarchical data that has a significant amount of variation at the person level. The traditional linear mixedeffects models assume that the residual variance is constant, which might not be true when the residual variance varies among individuals as well as in time. This thesis uses mixed-effects location-scale (MELS) models to model the mean and variance of an EMA outcome together. By introducing the possibility of variability in residual variance within and across individuals and with covariates, the MELS framework builds on LMMs. The analysis starts with a baseline LMM, followed by a MELS model to provide an analysis of predictors of both mean and variance. Maximum likelihood and numerical optimization techniques are used to estimate models in SAS. Diagnostic checks and parameter stability are used to evaluate convergence, while Akaike Information Criterion (AIC) is used to compare models. The results indicate significant within-person variation and better model fits for MELS approach.
Document Type
Thesis - unrestricted
Recommended Citation
Odero, Trenzy, "Modeling Mean and Variability of Anxiety in Ecological Momentary Assessment Data Using Mixed-Effects Location–Scale Models" (2026). Electronic Theses and Dissertations. Paper 4721. https://dc.etsu.edu/etd/4721
Copyright
Copyright by the authors.
Included in
Applied Statistics Commons, Longitudinal Data Analysis and Time Series Commons, Statistical Methodology Commons, Statistical Models Commons
