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A Practical Guide to Analyzing Time-Varying Associations between Physical Activity and Affect Using Multilevel Modeling

Kim, Jinhyuk ; Marcusson-Clavertz, David LU ; Togo, Fumiharu and Park, Hyuntae (2018) In Computational and Mathematical Methods in Medicine 2018.
Abstract

There is growing interest in within-person associations of objectively measured physical and physiological variables with psychological states in daily life. Here we provide a practical guide with SAS code of multilevel modeling for analyzing physical activity data obtained by accelerometer and self-report data from intensive and repeated measures using ecological momentary assessments (EMA). We review previous applications of EMA in research and clinical settings and the analytical tools that are useful for EMA research. We exemplify the analyses of EMA data with cases on physical activity data and affect and discuss the future challenges in the field.

Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Computational and Mathematical Methods in Medicine
volume
2018
article number
8652034
publisher
Hindawi Limited
external identifiers
  • pmid:30105083
  • scopus:85050820542
ISSN
1748-670X
DOI
10.1155/2018/8652034
language
English
LU publication?
yes
id
1d966ccc-aa9a-48fd-9aa1-dcd5740e9d7f
date added to LUP
2018-10-01 11:13:28
date last changed
2021-09-22 04:30:27
@article{1d966ccc-aa9a-48fd-9aa1-dcd5740e9d7f,
  abstract     = {<p>There is growing interest in within-person associations of objectively measured physical and physiological variables with psychological states in daily life. Here we provide a practical guide with SAS code of multilevel modeling for analyzing physical activity data obtained by accelerometer and self-report data from intensive and repeated measures using ecological momentary assessments (EMA). We review previous applications of EMA in research and clinical settings and the analytical tools that are useful for EMA research. We exemplify the analyses of EMA data with cases on physical activity data and affect and discuss the future challenges in the field.</p>},
  author       = {Kim, Jinhyuk and Marcusson-Clavertz, David and Togo, Fumiharu and Park, Hyuntae},
  issn         = {1748-670X},
  language     = {eng},
  publisher    = {Hindawi Limited},
  series       = {Computational and Mathematical Methods in Medicine},
  title        = {A Practical Guide to Analyzing Time-Varying Associations between Physical Activity and Affect Using Multilevel Modeling},
  url          = {http://dx.doi.org/10.1155/2018/8652034},
  doi          = {10.1155/2018/8652034},
  volume       = {2018},
  year         = {2018},
}