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Activity Number: 48
Type: Invited
Date/Time: Sunday, August 9, 2015 : 4:00 PM to 5:50 PM
Sponsor: Section on Statistics and the Environment
Abstract #314484
Title: The Modeling of Incomplete Cancer Incidence and Mortality Counts in Time and Space
Author(s): Jon Wakefield* and Laina Mercer
Companies: University of Washington and University of Washington
Keywords: Bayesian smoothing ; disease burden ; Markov random field models ; random walks ; space-time smoothing ;
Abstract:

Geo-referenced health data are often partially observed in the sense of there being a lack of a complete enumeration of all disease counts. In this talk I will describe the joint modeling of cancer incidence and mortality data across European countries. Many of these countries have incomplete data, for example, just sub-national incidence and mortality data, or mortality data only. Smoothing across time, space and age is leveraged, and mortality is modeled as a direct function of incidence. By directly linking incidence and mortality, national incidence data can be imputed when national mortality data only are available. This is joint work with Laina Mercer.


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