| Literature DB >> 31846119 |
Rachel Nordgren1, Donald Hedeker2, Genevieve Dunton3,4, Chih-Hsiang Yang4.
Abstract
Ecological Momentary Assessment data present some new modeling opportunities. Typically, there are sufficient data to explicitly model the within-subject (WS) variance, and in many applications, it is of interest to allow the WS variance to depend on covariates as well as random subject effects. We describe a model that allows multiple random effects per subject in the mean model (eg, random location intercept and slopes), as well as random scale in the error variance model. We present an example of the use of this model on a real dataset and a simulation study that shows the benefit of this model, relative to simpler approaches.Keywords: complex variation; heteroscedasticity; log-linear variance; multilevel; random effects; variance modeling
Mesh:
Year: 2019 PMID: 31846119 DOI: 10.1002/sim.8429
Source DB: PubMed Journal: Stat Med ISSN: 0277-6715 Impact factor: 2.373