Bayesian Analysis of Cancer Mortality Rates from Different Types and their Relative Occurrences

"We analyze mortality data from prostate, colon, lung, and all other types (called other cancer) to obtain age specific and age adjusted mortality rates for white males in the U.S. A related problem is to estimate the relative occurrences of these four types of cancer. We use Bayesian method be...

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Main Author: Delcroix, Sophie M.
Other Authors: Homer F. Walker, Department Head
Format: Others
Published: Digital WPI 1999
Subjects:
Online Access:https://digitalcommons.wpi.edu/etd-theses/1114
https://digitalcommons.wpi.edu/cgi/viewcontent.cgi?article=2113&context=etd-theses
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spelling ndltd-wpi.edu-oai-digitalcommons.wpi.edu-etd-theses-21132019-03-22T05:45:15Z Bayesian Analysis of Cancer Mortality Rates from Different Types and their Relative Occurrences Delcroix, Sophie M. "We analyze mortality data from prostate, colon, lung, and all other types (called other cancer) to obtain age specific and age adjusted mortality rates for white males in the U.S. A related problem is to estimate the relative occurrences of these four types of cancer. We use Bayesian method because it permits a degree of smoothing which is needed to analyze data at a small area level and to assess the patterns. In the recent Atlas of the United States Mortality (1996) each type of cancer was analyzed individually. The difficulty in doing so is that there are many small areas with zero deaths. We conjecture that simultaneous analyses might help to overcome this problem, and at the same time to estimate the relative occurrences. We start with a Poisson model for the deaths, which produces a likelihood function that separates into two parts: a Poisson likelihood for the rates and a multinomial likelihood for the relative occurrences. These permit the use of a standard Poisson regression model on age as in Nandram, Sedransk and Pickle (1999), and the novelty is a multivariate logit model on the relative occurrences in which per capita income, the percent of people below poverty level, education (percent of people with four years of college) and two criteria pollutants, EPAPM25 and EPASO2, are used as covariates. We fitted the models using Markov chain Monte Carlo methods. We used one of the models to present maps of occurrences and rates for the four types. An alternative model did not work well because it provides the same pattern by age and disease. We found that while EPAPM25 has a negative effect on the occurrences, EPASO2 has a positive effect. Also, we found some interesting patterns associated with the geographical variations of mortality rates and the relative occurrences of the four cancer types." 1999-12-14T08:00:00Z text application/pdf https://digitalcommons.wpi.edu/etd-theses/1114 https://digitalcommons.wpi.edu/cgi/viewcontent.cgi?article=2113&context=etd-theses Masters Theses (All Theses, All Years) Digital WPI Homer F. Walker, Department Head Balgobin Nandram, Advisor Hyunjoong Kim Bayesian method mapping Bayesian statistical decision theory Cancer Statistics
collection NDLTD
format Others
sources NDLTD
topic Bayesian method
mapping
Bayesian statistical decision theory
Cancer
Statistics
spellingShingle Bayesian method
mapping
Bayesian statistical decision theory
Cancer
Statistics
Delcroix, Sophie M.
Bayesian Analysis of Cancer Mortality Rates from Different Types and their Relative Occurrences
description "We analyze mortality data from prostate, colon, lung, and all other types (called other cancer) to obtain age specific and age adjusted mortality rates for white males in the U.S. A related problem is to estimate the relative occurrences of these four types of cancer. We use Bayesian method because it permits a degree of smoothing which is needed to analyze data at a small area level and to assess the patterns. In the recent Atlas of the United States Mortality (1996) each type of cancer was analyzed individually. The difficulty in doing so is that there are many small areas with zero deaths. We conjecture that simultaneous analyses might help to overcome this problem, and at the same time to estimate the relative occurrences. We start with a Poisson model for the deaths, which produces a likelihood function that separates into two parts: a Poisson likelihood for the rates and a multinomial likelihood for the relative occurrences. These permit the use of a standard Poisson regression model on age as in Nandram, Sedransk and Pickle (1999), and the novelty is a multivariate logit model on the relative occurrences in which per capita income, the percent of people below poverty level, education (percent of people with four years of college) and two criteria pollutants, EPAPM25 and EPASO2, are used as covariates. We fitted the models using Markov chain Monte Carlo methods. We used one of the models to present maps of occurrences and rates for the four types. An alternative model did not work well because it provides the same pattern by age and disease. We found that while EPAPM25 has a negative effect on the occurrences, EPASO2 has a positive effect. Also, we found some interesting patterns associated with the geographical variations of mortality rates and the relative occurrences of the four cancer types."
author2 Homer F. Walker, Department Head
author_facet Homer F. Walker, Department Head
Delcroix, Sophie M.
author Delcroix, Sophie M.
author_sort Delcroix, Sophie M.
title Bayesian Analysis of Cancer Mortality Rates from Different Types and their Relative Occurrences
title_short Bayesian Analysis of Cancer Mortality Rates from Different Types and their Relative Occurrences
title_full Bayesian Analysis of Cancer Mortality Rates from Different Types and their Relative Occurrences
title_fullStr Bayesian Analysis of Cancer Mortality Rates from Different Types and their Relative Occurrences
title_full_unstemmed Bayesian Analysis of Cancer Mortality Rates from Different Types and their Relative Occurrences
title_sort bayesian analysis of cancer mortality rates from different types and their relative occurrences
publisher Digital WPI
publishDate 1999
url https://digitalcommons.wpi.edu/etd-theses/1114
https://digitalcommons.wpi.edu/cgi/viewcontent.cgi?article=2113&context=etd-theses
work_keys_str_mv AT delcroixsophiem bayesiananalysisofcancermortalityratesfromdifferenttypesandtheirrelativeoccurrences
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