Cargando…
Using Bayesian statistics for modeling PTSD through Latent Growth Mixture Modeling: implementation and discussion
BACKGROUND: After traumatic events, such as disaster, war trauma, and injuries including burns (which is the focus here), the risk to develop posttraumatic stress disorder (PTSD) is approximately 10% (Breslau & Davis, 1992). Latent Growth Mixture Modeling can be used to classify individuals into...
Autores principales: | Depaoli, Sarah, van de Schoot, Rens, van Loey, Nancy, Sijbrandij, Marit |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Co-Action Publishing
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4348411/ https://www.ncbi.nlm.nih.gov/pubmed/25735415 http://dx.doi.org/10.3402/ejpt.v6.27516 |
Ejemplares similares
-
Latent trajectory studies: the basics, how to interpret the results, and what to report
por: van de Schoot, Rens
Publicado: (2015) -
Applications of Latent Growth Mixture Modeling and allied methods to posttraumatic stress response data
por: Galatzer-Levy, Isaac R.
Publicado: (2015) -
Latent Growth Mixture Models to estimate PTSD trajectories
por: Van de Schoot, Rens
Publicado: (2015) -
Cognitive Predictors of Grief Trajectories in the First Months of Loss: A Latent Growth Mixture Model
por: Smith, Kirsten V., et al.
Publicado: (2019) -
The neurobiology of PTSD
por: Lanius, Ruth, et al.
Publicado: (2017)