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Extensions to Multivariate Space Time Mixture Modeling of Small Area Cancer Data

Oral cavity and pharynx cancer, even when considered together, is a fairly rare disease. Implementation of multivariate modeling with lung and bronchus cancer, as well as melanoma cancer of the skin, could lead to better inference for oral cavity and pharynx cancer. The multivariate structure of the...

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Detalles Bibliográficos
Autores principales: Carroll, Rachel, Lawson, Andrew B., Faes, Christel, Kirby, Russell S., Aregay, Mehreteab, Watjou, Kevin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5451954/
https://www.ncbi.nlm.nih.gov/pubmed/28486417
http://dx.doi.org/10.3390/ijerph14050503
Descripción
Sumario:Oral cavity and pharynx cancer, even when considered together, is a fairly rare disease. Implementation of multivariate modeling with lung and bronchus cancer, as well as melanoma cancer of the skin, could lead to better inference for oral cavity and pharynx cancer. The multivariate structure of these models is accomplished via the use of shared random effects, as well as other multivariate prior distributions. The results in this paper indicate that care should be taken when executing these types of models, and that multivariate mixture models may not always be the ideal option, depending on the data of interest.