A General Framework for the Inclusion of Time-Varying and Time-Invariant Covariates in Latent State Trait Models
This article is a preprint and has not been certified by peer review [What does this mean?].
Author(s) / Creator(s)
Oeltjen, Lara
Koch, Tobias
Holtmann, Jana
Eid, Michael
Nussbeck, Fridtjof
Abstract / Description
Latent state-trait (LST) models are increasingly applied in psychology. However, existing LST models are limited and do not allow researchers to relate time-varying or time-invariant covariates, or a combination of both, to key parameters in LST models. We present a general framework for the inclusion of nominal and/or continuous time-varying and time-invariant covariates in LST models. The new framework builds on modern LST theory and Bayesian moderated nonlinear factor analysis and is termed moderated nonlinear LST (MN-LST) framework. The MN-LST framework offers new modeling possibilities and allows for a fine-grained analysis of trait change, synergistic interaction effects, as well as inter- or intra- individual variability. The new MN-LST approach is compared to multiple-indicator latent growth curve models. The advantages of the MN-LST are illustrated in an empirical application examining dyadic coping in romantic relationships. Finally, the advantages and limitations of the approach are discussed, and practical recommendations are provided.
Keyword(s)
latent state-trait models moderated nonlinear factor analysis time-varying covariates time-invariant covariates synergistic interaction effectsPersistent Identifier
Date of first publication
2020-09
Publisher
PsychArchives
Citation
Oeltjen, L., Koch, T., Holtmann, J., Eid, M., & Nussbeck, F. (2020). A General Framework for the Inclusion of Time-Varying and Time-Invariant Covariates in Latent State Trait Models. PsychArchives. https://doi.org/10.23668/PSYCHARCHIVES.4194
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MNLST_draft_2020_09_04_.pdfAdobe PDF - 1.26MBMD5: a75a2c906d76ac1ae58ddc962d70a4d9
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There are no other versions of this object.
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Author(s) / Creator(s)Oeltjen, Lara
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Author(s) / Creator(s)Koch, Tobias
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Author(s) / Creator(s)Holtmann, Jana
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Author(s) / Creator(s)Eid, Michael
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Author(s) / Creator(s)Nussbeck, Fridtjof
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PsychArchives acquisition timestamp2020-09-30T12:01:04Z
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Made available on2020-09-30T12:01:04Z
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Date of first publication2020-09
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Submission date2020-09
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Abstract / DescriptionLatent state-trait (LST) models are increasingly applied in psychology. However, existing LST models are limited and do not allow researchers to relate time-varying or time-invariant covariates, or a combination of both, to key parameters in LST models. We present a general framework for the inclusion of nominal and/or continuous time-varying and time-invariant covariates in LST models. The new framework builds on modern LST theory and Bayesian moderated nonlinear factor analysis and is termed moderated nonlinear LST (MN-LST) framework. The MN-LST framework offers new modeling possibilities and allows for a fine-grained analysis of trait change, synergistic interaction effects, as well as inter- or intra- individual variability. The new MN-LST approach is compared to multiple-indicator latent growth curve models. The advantages of the MN-LST are illustrated in an empirical application examining dyadic coping in romantic relationships. Finally, the advantages and limitations of the approach are discussed, and practical recommendations are provided.en
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Publication statusotheren
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Review statusnotRevieweden
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CitationOeltjen, L., Koch, T., Holtmann, J., Eid, M., & Nussbeck, F. (2020). A General Framework for the Inclusion of Time-Varying and Time-Invariant Covariates in Latent State Trait Models. PsychArchives. https://doi.org/10.23668/PSYCHARCHIVES.4194en
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Persistent Identifierhttps://hdl.handle.net/20.500.12034/3806
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Persistent Identifierhttps://doi.org/10.23668/psycharchives.4194
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Language of contenteng
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PublisherPsychArchivesen
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Keyword(s)latent state-trait modelsen
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Keyword(s)moderated nonlinear factor analysisen
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Keyword(s)time-varying covariatesen
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Keyword(s)time-invariant covariatesen
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Keyword(s)synergistic interaction effectsen
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Dewey Decimal Classification number(s)150
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TitleA General Framework for the Inclusion of Time-Varying and Time-Invariant Covariates in Latent State Trait Modelsen
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DRO typepreprinten
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Leibniz subject classificationPsychologiede_DE