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Bayesian Hierarchical Modeling for Categorical Longitudinal Data from Sedation Measurements
We investigate a Bayesian hierarchical model for the analysis of categorical longitudinal data from sedation measurement for Magnetic Resonance Imaging (MRI) and Computerized Tomography (CT). Data for each patient is observed at different time points within the time up to 60 min. A model for the sed...
Autores principales: | Terzi, Erol, Cengiz, Mehmet Ali |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3722845/ https://www.ncbi.nlm.nih.gov/pubmed/23935702 http://dx.doi.org/10.1155/2013/579214 |
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