[-] Show simple item record

dc.contributor.advisorSun, Dongchueng
dc.contributor.authorDu, Jiangeng
dc.date.issued2018eng
dc.date.submitted2018 Springeng
dc.description.abstractData on cancer in the United States is collected through cancer registries. The Missouri Cancer Registry and Research Center (MCR-ARC) maintains a statewide cancer surveillance system and participate in research in support of the prevention of cancer and the reduction of the cancer burden among Missouri residents. We applied Bayesian hierarchical models to colorectal cancer (CRC) and breast cancer related data collected by the MCR-ARC. In the first project, CRC incidence and mortality rates in Missouri were studied with emphasis on different groups of people categorized by age, gender and county at diagnosis. The incidence and mortality data were aggregated into different spatial regions due to data confidential requirements, which was identified as a misaligned-region problem in multivariate disease mapping literature. The Marginally and Conditionally CAR models were built to address the problem. Later on, colorectal cancer screening (CRCS) prevalences were analyzed due to its importance to the early detection of CRC. We applied small area estimation techniques to produce county-level CRCS prevalences from the state-level Behavioral Risk Factor Surveillance System (BRFSS) data. The last two projects focused on breast cancer related data. One is about breast cancer survival analysis in Missouri with emphasis on detecting the spatial variation of survival time among counties in Missouri, after accounting for the differences in demographic and cancer stages. The other one is studying the disparities of breast cancer treatment delay with respect to patient's race, age, stage of cancer, county at diagnosis and year of diagnosis.eng
dc.identifier.urihttps://hdl.handle.net/10355/66162
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartofcollectionUniversity of Missouri--Columbia. Graduate School. Theses and Dissertationseng
dc.rightsOpenAccesseng
dc.rights.licenseThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Licenseeng
dc.titleBayesian hierarchical modeling of colorectal and breast cancer data in Missourieng
dc.typeThesiseng
thesis.degree.disciplineStatistics (MU)eng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.levelDoctoraleng
thesis.degree.namePh. D.eng


Files in this item

[PDF]

This item appears in the following Collection(s)

[-] Show simple item record