Piecewise latent growth models: beyond modeling linear-linear processes.
Conditionally-linear growth models
Multiphase
Spline
Structured latent curve model
Journal
Behavior research methods
ISSN: 1554-3528
Titre abrégé: Behav Res Methods
Pays: United States
ID NLM: 101244316
Informations de publication
Date de publication:
04 2021
04 2021
Historique:
pubmed:
12
8
2020
medline:
8
6
2021
entrez:
12
8
2020
Statut:
ppublish
Résumé
Piecewise latent growth models (LGMs) for linear-linear processes have been well-documented and studied in recent years. However, in the latent growth modeling literature, advancements to other functional forms as well as to multiple changepoints or knots have been nearly non-existent. This manuscript deals with three extensions. The first is to a piecewise latent growth model incorporating higher-order polynomials. The second is to extend the basic framework to three phases. The last extension is to inherently nonlinear functions. In these extensions, the changepoint(s) is a parameter to be estimated and may be fixed or allowed to vary across subjects as an application warrants. The approaches are developed and two illustrative empirical examples from psychology are used to highlight the methodological nuances. Annotated statistical software is provided to make these elaborations accessible to practitioners and methodologists.
Identifiants
pubmed: 32779105
doi: 10.3758/s13428-020-01420-5
pii: 10.3758/s13428-020-01420-5
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
593-608Références
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