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Bayesian Inference for Growth Mixture Models with Latent Class Dependent Missing Data
Growth mixture models (GMMs) with nonignorable missing data have drawn increasing attention in research communities but have not been fully studied. The goal of this article is to propose and to evaluate a Bayesian method to estimate the GMMs with latent class dependent missing data. An extended GMM...
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| Hauptverfasser: | , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
2011
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4002129/ https://ncbi.nlm.nih.gov/pubmed/24790248 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/00273171.2011.589261 |
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