Variance constraints strongly influenced model performance in growth mixture modeling: a simulation and empirical study

BACKGROUND: Growth Mixture Modeling (GMM) is commonly used to group individuals on their development over time, but convergence issues and impossible values are common. This can result in unreliable model estimates. Constraining variance parameters across classes or over time can solve these issues,...

Descripción completa

Detalles Bibliográficos
Autores principales: Sijbrandij, Jitske J., Hoekstra, Tialda, Almansa, Josué, Peeters, Margot, Bültmann, Ute, Reijneveld, Sijmen A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7659099/
https://www.ncbi.nlm.nih.gov/pubmed/33183230
http://dx.doi.org/10.1186/s12874-020-01154-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7659099/
https://www.ncbi.nlm.nih.gov/pubmed/33183230
http://dx.doi.org/10.1186/s12874-020-01154-0

Ejemplares similares