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A Practical Guide to Analyzing Time-Varying Associations between Physical Activity and Affect Using Multilevel Modeling
Penn State Univ, USA.
Penn State Univ, USA;Lund University, Sweden.ORCID iD: 0000-0002-0730-9954
Univ Tokyo, Japan.
Dong A Univ, Republic of Korea.ORCID iD: 0000-0002-1976-0005
2018 (English)In: Computational & Mathematical Methods in Medicine, ISSN 1748-670X, E-ISSN 1748-6718, Vol. 2018, article id 8652034Article, review/survey (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Hindawi Publishing Corporation, 2018. Vol. 2018, article id 8652034
National Category
Psychology
Research subject
Social Sciences, Psychology
Identifiers
URN: urn:nbn:se:lnu:diva-112750DOI: 10.1155/2018/8652034ISI: 000439799200001PubMedID: 30105083Scopus ID: 2-s2.0-85050820542OAI: oai:DiVA.org:lnu-112750DiVA, id: diva2:1656663
Available from: 2022-05-06 Created: 2022-05-06 Last updated: 2023-05-03Bibliographically approved

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Marcusson-Clavertz, David

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