title: Bayesian model selection methods in modeling small area colon cancer incidence.
abstract: OBJECTIVE
  Many types of cancer have an underlying spatial incidence distribution. Spatial model selection methods can be useful when determining the linear predictor that best describes incidence outcomes.
  
  
  METHODS
  In this article, we examine the applications and benefits of using two different types of spatial model selection techniques, Bayesian model selection and Bayesian model averaging, in relation to colon cancer incidence in the state of Georgia, United States.
  
  
  RESULTS
  Both methods produce useful results that lead to the determination that median household income and percent African American population are important predictors of colon cancer incidence in the Northern counties of the state, whereas percent persons below poverty level and percent African American population are important in the Southern counties.
  
  
  CONCLUSIONS
  Of the two presented methods, Bayesian model selection appears to provide more succinct results, but applying the two in combination offers even more useful information into the spatial preferences of the alternative linear predictors.
authors.affiliation: Department of Public Health, Medical University of South Carolina, Charleston. Electronic address: mosra@musc.edu.
authors.forename: Rachel
authors.initials: R
authors.lastname: Carroll
authors.affiliation: Department of Public Health, Medical University of South Carolina, Charleston.
authors.forename: Andrew B
authors.initials: AB
authors.lastname: Lawson
authors.affiliation: Interuniversity Institute for Statistics and Statistical Bioinformatics, Hasselt University, Diepenbeek, Belgium.
authors.forename: Christel
authors.initials: C
authors.lastname: Faes
authors.affiliation: Department of Community and Family Health, University of South Florida, Tampa.
authors.forename: Russell S
authors.initials: RS
authors.lastname: Kirby
authors.affiliation: Department of Public Health, Medical University of South Carolina, Charleston.
authors.forename: Mehreteab
authors.initials: M
authors.lastname: Aregay
authors.affiliation: Interuniversity Institute for Statistics and Statistical Bioinformatics, Hasselt University, Diepenbeek, Belgium.
authors.forename: Kevin
authors.initials: K
authors.lastname: Watjou
mesh_terms: D001499:Bayes Theorem; D003110:Colonic Neoplasms / Q000191:economics / Q000453:epidemiology*; D005006:Ethnicity; D005845:Georgia / Q000453:epidemiology; D006801:Humans; D015994:Incidence; D015233:Models, Statistical; D011204:Poverty Areas; D062206:Spatial Analysis
keywords: Bayesian model averaging; Bayesian model selection; Colon cancer; MCMC; Spatial regression