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Extending the mixed‐effects model to consider within‐subject variance for Ecological Momentary Assessment data
Author(s) -
Nordgren Rachel,
Hedeker Donald,
Dunton Genevieve,
Yang ChihHsiang
Publication year - 2019
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.8429
Subject(s) - variance (accounting) , covariate , random effects model , computer science , subject (documents) , mixed model , statistics , scale (ratio) , econometrics , ecology , mathematics , machine learning , geography , medicine , meta analysis , accounting , cartography , library science , business , biology
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.