Modeling between-subject and within-subject variances in ecological momentary assessment data using mixed-effects location scale models
Ecological momentary assessment and/or experience sampling methods are increasingly used in health studies to study subjective experiences within changing environmental contexts. In these studies, up to 30 or 40 observations are often obtained for each subject. Because there are so many measurements...
Saved in:
Published in | Statistics in medicine Vol. 31; no. 27; pp. 3328 - 3336 |
---|---|
Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Chichester, UK
John Wiley & Sons, Ltd
30.11.2012
Wiley Subscription Services, Inc |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Ecological momentary assessment and/or experience sampling methods are increasingly used in health studies to study subjective experiences within changing environmental contexts. In these studies, up to 30 or 40 observations are often obtained for each subject. Because there are so many measurements per subject, one can characterize a subject's mean and variance and can specify models for both. In this article, we focus on an adolescent smoking study using ecological momentary assessment 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. 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. Copyright © 2012 John Wiley & Sons, Ltd. |
---|---|
Bibliography: | ArticleID:SIM5338 istex:9826E3FCBED5D9CD38A0CDC9B4AA021CAD390D6E ark:/67375/WNG-17MB27WR-1 National Cancer Institute - No. P01CA098262; No. R21CA140696 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0277-6715 1097-0258 1097-0258 |
DOI: | 10.1002/sim.5338 |