Multiple imputation of longitudinal categorical data through bayesian mixture latent Markov models

Standard latent class modeling has recently been shown to provide a flexible tool for the multiple imputation (MI) of missing categorical covariates in cross-sectional studies. This article introduces an analogous tool for longitudinal studies: MI using Bayesian mixture Latent Markov (BMLM) models....

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Detalles Bibliográficos
Autores principales: Vidotto, Davide, Vermunt, Jeroen K., Van Deun, Katrijn
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2019
Materias:
Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9041790/
https://www.ncbi.nlm.nih.gov/pubmed/35707130
http://dx.doi.org/10.1080/02664763.2019.1692794

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9041790/
https://www.ncbi.nlm.nih.gov/pubmed/35707130
http://dx.doi.org/10.1080/02664763.2019.1692794

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