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http://hdl.handle.net/1942/26534
Title: | Spatially-dependent Bayesian model selection for disease mapping | Authors: | Carroll, Rachel LAWSON, Andrew FAES, Christel Kirby, Russell S. AREGAY, Mehreteab WATJOU, Kevin |
Issue Date: | 2018 | Publisher: | SAGE PUBLICATIONS LTD | Source: | STATISTICAL METHODS IN MEDICAL RESEARCH, 27(1), p. 250-268 | Abstract: | In disease mapping where predictor effects are to be modeled, it is often the case that sets of predictors are fixed, and the aim is to choose between fixed model sets. Model selection methods, both Bayesian model selection and Bayesian model averaging, are approaches within the Bayesian paradigm for achieving this aim. In the spatial context, model selection could have a spatial component in the sense that some models may be more appropriate for certain areas of a study region than others. In this work, we examine the use of spatially referenced Bayesian model averaging and Bayesian model selection via a large-scale simulation study accompanied by a small-scale case study. Our results suggest that BMS performs well when a strong regression signature is found. | Notes: | [Carroll, Rachel; Lawson, Andrew B.; Aregay, Mehreteab] Med Univ South Carolina, Dept Publ Hlth, 135 Cannon St, Charleston, SC 29425 USA. [Faes, Christel; Watjou, Kevin] Hasselt Univ, Interuniv Inst Stat & Stat Bioinformat, Diepenbeek, Belgium. [Kirby, Russell S.] Univ S Florida, Dept Community & Family Hlth, Tampa, FL USA. | Keywords: | Bayesian model averaging; Bayesian model selection; spatial; R2WinBUGS; BRugs; MCMC;Bayesian model averaging; Bayesian model selection; spatial; R2WinBUGS; BRugs; MCMC | Document URI: | http://hdl.handle.net/1942/26534 | ISSN: | 0962-2802 | e-ISSN: | 1477-0334 | DOI: | 10.1177/0962280215627298 | ISI #: | 000419874400018 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2019 |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
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caroll 1.pdf | Peer-reviewed author version | 1.52 MB | Adobe PDF | View/Open |
0962280215627298.pdf Restricted Access | Published version | 1.45 MB | Adobe PDF | View/Open Request a copy |
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