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Bayesian Multilevel Latent Class Models for the Multiple Imputation of Nested Categorical Data
With this article, we propose using a Bayesian multilevel latent class (BMLC; or mixture) model for the multiple imputation of nested categorical data. Unlike recently developed methods that can only pick up associations between pairs of variables, the multilevel mixture model we propose is flexible...
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| Gepubliceerd in: | J Educ Behav Stat |
|---|---|
| Hoofdauteurs: | , , |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
SAGE Publications
2018
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| Onderwerpen: | |
| Online toegang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6187066/ https://ncbi.nlm.nih.gov/pubmed/30369783 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3102/1076998618769871 |
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