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Int. J. Environ. Res. Public Health 2017, 14(5), 503; doi:10.3390/ijerph14050503

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

1
Department of Public Health Sciences, Medical University of South Carolina, 135 Cannon St, Charleston, SC 29425, USA
2
Interuniversity Institute for Statistics and Statistical Bioinformatics, Hasselt University, 3500 Hasselt, Belgium
3
Department of Community and Family Health, University of South Florida, Tampa, FL 33620, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Louise Ryan and Craig Anderson
Received: 6 February 2017 / Revised: 3 May 2017 / Accepted: 5 May 2017 / Published: 9 May 2017
(This article belongs to the Special Issue Spatial Modelling for Public Health Research)
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Abstract

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. View Full-Text
Keywords: lung and bronchus cancer; melanoma cancer of the skin; oral cavity and pharynx cancer; incidence; mixture model; spatio-temporal; disease mapping lung and bronchus cancer; melanoma cancer of the skin; oral cavity and pharynx cancer; incidence; mixture model; spatio-temporal; disease mapping
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Carroll, R.; Lawson, A.B.; Faes, C.; Kirby, R.S.; Aregay, M.; Watjou, K. Extensions to Multivariate Space Time Mixture Modeling of Small Area Cancer Data. Int. J. Environ. Res. Public Health 2017, 14, 503.

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