Online Program

Complex longitudinal model applied in Ecological Momentary Assessment (EMA) Data

Donald Hedeker, University of Illinois at Chicago 
*Xue Li, Hines Cooperative Studies Program Coordinating Center, VA Hospital 

Keywords: Heteroscedasticity; Log-linear variance; 3-level location scale model; Variance modeling; PROC NLMIXED

In studies using Ecological Momentary Assessment (EMA), or other intensive longitudinal data collection methods, interest frequently centers on changes in the variances, both within-subjects (WS) and between-subjects (BS). For this, Hedeker et al. (2008) developed a 2-level mixed model that treats observations as being nested within subjects and allows covariates to influence both the WS and BS variance, beyond their influence on means. However, in EMA studies, subjects often provide many responses within and across days. To account for the possible systematic day-to-day variation, we developed a 3-level mixed location scale model that treats observations within days within subjects, and allows covariates to influence the variance at the subject, day, and observation level (over and above their usual effects on means) using a log-linear representation. We provide details of a marginal maximum likelihood (ML) solution and demonstrate how SAS PROC NLMIXED can be used to obtain ML estimates in an alternative parameterization of our proposed 3-level model. The accuracy of this approach using NLMIXED was verified by simulation studies. Data from an adolescent smoking study using EMA was analyzed to demonstrate this approach. The analyses clearly showed the benefit of the proposed 3-level model over the existing 2-level approach.