Modeling and Predicting Complex Patterns of Change Using Growth Component Models: An Application to Depression Trajectories in Cancer Patients Article Swipe
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· 2019
· Open Access
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· DOI: https://doi.org/10.31234/osf.io/6kd3w
In this paper, we present a general and flexible framework for constructively defining growth components to model complex change processes. Building on the concepts of the latent state-trait theory (LST theory; Steyer, Ferring, & Schmitt, 1992), we develop structural equation models containing latent variables that represent latent growth (change) components of interest. We formulate these models based on an approach presented by Mayer, Steyer & Mueller (in press). We discuss an application to the longitudinal course of depression in 2794 individuals from the Health and Retirement Study who experienced cancer diagnosis over the course of the study. We found that (1) on average, the depression trajectories showed a steep increase after diagnosis as well as an adaptation phase where levels returned back to levels prior to diagnosis, and (2) individual differences in change were large and could be partly explained by marital status and cognitive functioning.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.31234/osf.io/6kd3w
- OA Status
- gold
- References
- 20
- Related Works
- 10
- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W4245955215Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.31234/osf.io/6kd3wDigital Object Identifier
- Title
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Modeling and Predicting Complex Patterns of Change Using Growth Component Models: An Application to Depression Trajectories in Cancer PatientsWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2019Year of publication
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2019-10-12Full publication date if available
- Authors
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Axel Mayer, Christian Geiser, Frank J. Infurna, Christiane FiegeList of authors in order
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https://doi.org/10.31234/osf.io/6kd3wPublisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.31234/osf.io/6kd3wDirect OA link when available
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Latent growth modeling, Trait, Depression (economics), Latent variable, Structural equation modeling, Psychology, Cognition, Econometrics, Developmental psychology, Cognitive psychology, Mathematics, Statistics, Computer science, Psychiatry, Economics, Programming language, MacroeconomicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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20Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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