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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....
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Taylor & Francis
2019
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| Materias: | |
| 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 |