Minimum required sample size for modelling daily cyclic patterns in ecological momentary assessment data
Author(s) / Creator(s)
van de Maat, Robin
Lataster, Johan
Verboon, Peter
Abstract / Description
Cyclical patterns in ecological momentary assessment (EMA) data on emotions have remained relatively underresearched. Addressing such patterns can help to better understand emotion dynamics across time and contexts. However, no general rules of thumb are readily available for psychological researchers to determine the required sample size for measuring cyclical patterns in emotions. This study, therefore, estimates the minimum required sample sizes—in terms of the number of measurements per time period and subjects—to obtain a power of 80% given a certain underlying cyclical pattern based on input parameter values derived from an empirical EMA dataset. Estimated minimum required sample sizes varied between 50 subjects and 10 measurements per subject for accurately detecting cyclical patterns with a large magnitude, to 60 subjects and 30 measurements per subject for cyclical patterns of small magnitude. The resulting rules of thumb for sample sizes are discussed with a number of considerations in mind.
Keyword(s)
ecological momentary assessment experience sampling method ambulatory assessment intensive longitudinal data cyclic models sample sizesPersistent Identifier
Date of first publication
2024-12-23
Journal title
Methodology
Volume
20
Issue
4
Page numbers
265–282
Publisher
PsychOpen GOLD
Publication status
publishedVersion
Review status
peerReviewed
Is version of
Citation
van de Maat, R., Lataster, J., & Verboon, P. (2024). Minimum required sample size for modelling daily cyclic patterns in ecological momentary assessment data. Methodology, 20(4), 265-282. https://doi.org/10.5964/meth.11399
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Author(s) / Creator(s)van de Maat, Robin
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Author(s) / Creator(s)Lataster, Johan
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Author(s) / Creator(s)Verboon, Peter
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PsychArchives acquisition timestamp2025-04-25T11:32:57Z
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Made available on2025-04-25T11:32:57Z
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Date of first publication2024-12-23
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Abstract / DescriptionCyclical patterns in ecological momentary assessment (EMA) data on emotions have remained relatively underresearched. Addressing such patterns can help to better understand emotion dynamics across time and contexts. However, no general rules of thumb are readily available for psychological researchers to determine the required sample size for measuring cyclical patterns in emotions. This study, therefore, estimates the minimum required sample sizes—in terms of the number of measurements per time period and subjects—to obtain a power of 80% given a certain underlying cyclical pattern based on input parameter values derived from an empirical EMA dataset. Estimated minimum required sample sizes varied between 50 subjects and 10 measurements per subject for accurately detecting cyclical patterns with a large magnitude, to 60 subjects and 30 measurements per subject for cyclical patterns of small magnitude. The resulting rules of thumb for sample sizes are discussed with a number of considerations in mind.en_US
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Publication statuspublishedVersion
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Review statuspeerReviewed
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Citationvan de Maat, R., Lataster, J., & Verboon, P. (2024). Minimum required sample size for modelling daily cyclic patterns in ecological momentary assessment data. Methodology, 20(4), 265-282. https://doi.org/10.5964/meth.11399
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ISSN1614-2241
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Persistent Identifierhttps://hdl.handle.net/20.500.12034/11694
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Persistent Identifierhttps://doi.org/10.23668/psycharchives.16282
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Language of contenteng
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PublisherPsychOpen GOLD
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Is version ofhttps://doi.org/10.5964/meth.11399
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Keyword(s)ecological momentary assessmenten_US
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Keyword(s)experience sampling methoden_US
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Keyword(s)ambulatory assessmenten_US
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Keyword(s)intensive longitudinal dataen_US
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Keyword(s)cyclic modelsen_US
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Keyword(s)sample sizesen_US
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Dewey Decimal Classification number(s)150
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TitleMinimum required sample size for modelling daily cyclic patterns in ecological momentary assessment dataen_US
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DRO typearticle
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Issue4
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Journal titleMethodology
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Page numbers265–282
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Volume20
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Visible tag(s)Version of Record