Matches in SemOpenAlex for { <https://semopenalex.org/work/W2010131696> ?p ?o ?g. }
Showing items 1 to 89 of
89
with 100 items per page.
- W2010131696 abstract "Multivariate data summarized over areal units (counties, zip codes, etc.) are common in the field of public health. Estimation or testing of geographic boundaries for such data may have varied goals. For example, for data on multiple disease outcomes, we may be interested in a single set of composite boundaries for all diseases, separate boundaries for each disease, or both. Different areal wombling (boundary analysis) techniques are needed to meet these different requirements. But in any case, the underlying statistical model needs to account for correlations across both diseases and locations. Utilizing recent developments in multivariate conditionally autoregressive (MCAR) distributions and spatial structural equation modeling, we suggest a variety of Bayesian hierarchical models for multivariate areal boundary analysis, including some that incorporate random neighborhood structure. Many of our models can be implemented via standard software, namely WinBUGS for posterior sampling and $R$ for summarization and plotting. We illustrate our methods using Minnesota county-level esophagus, larynx, and lung cancer data, comparing models that account for both, only one, or neither of the aforementioned correlations. We identify both composite and cancer-specific boundaries, selecting the best statistical model using the DIC criterion. Our results indicate primary boundaries in both the composite and cancer-specific response surface separating the mining- and tourism-oriented northeast counties from the remainder of the state, as well as secondary (residual) boundaries in the Twin Cities metro area." @default.
- W2010131696 created "2016-06-24" @default.
- W2010131696 creator A5012243539 @default.
- W2010131696 creator A5036817879 @default.
- W2010131696 date "2007-06-01" @default.
- W2010131696 modified "2023-09-23" @default.
- W2010131696 title "Bayesian multivariate areal wombling for multiple disease boundary analysis" @default.
- W2010131696 cites W1985905165 @default.
- W2010131696 cites W2004014822 @default.
- W2010131696 cites W2020999234 @default.
- W2010131696 cites W2022928697 @default.
- W2010131696 cites W2036837650 @default.
- W2010131696 cites W2040303896 @default.
- W2010131696 cites W2046225363 @default.
- W2010131696 cites W2057765075 @default.
- W2010131696 cites W2073222618 @default.
- W2010131696 cites W2083273808 @default.
- W2010131696 cites W2091300140 @default.
- W2010131696 cites W2102349058 @default.
- W2010131696 cites W2114100577 @default.
- W2010131696 cites W2114192876 @default.
- W2010131696 cites W2114220616 @default.
- W2010131696 cites W2121101292 @default.
- W2010131696 cites W2131531229 @default.
- W2010131696 cites W2151372718 @default.
- W2010131696 cites W2161132263 @default.
- W2010131696 cites W2496675188 @default.
- W2010131696 cites W4234195429 @default.
- W2010131696 cites W4301341693 @default.
- W2010131696 doi "https://doi.org/10.1214/07-ba211" @default.
- W2010131696 hasPublicationYear "2007" @default.
- W2010131696 type Work @default.
- W2010131696 sameAs 2010131696 @default.
- W2010131696 citedByCount "39" @default.
- W2010131696 countsByYear W20101316962012 @default.
- W2010131696 countsByYear W20101316962013 @default.
- W2010131696 countsByYear W20101316962014 @default.
- W2010131696 countsByYear W20101316962015 @default.
- W2010131696 countsByYear W20101316962016 @default.
- W2010131696 countsByYear W20101316962017 @default.
- W2010131696 countsByYear W20101316962018 @default.
- W2010131696 countsByYear W20101316962019 @default.
- W2010131696 countsByYear W20101316962020 @default.
- W2010131696 countsByYear W20101316962021 @default.
- W2010131696 countsByYear W20101316962022 @default.
- W2010131696 countsByYear W20101316962023 @default.
- W2010131696 crossrefType "journal-article" @default.
- W2010131696 hasAuthorship W2010131696A5012243539 @default.
- W2010131696 hasAuthorship W2010131696A5036817879 @default.
- W2010131696 hasBestOaLocation W20101316961 @default.
- W2010131696 hasConcept C105795698 @default.
- W2010131696 hasConcept C107673813 @default.
- W2010131696 hasConcept C124101348 @default.
- W2010131696 hasConcept C134306372 @default.
- W2010131696 hasConcept C158424031 @default.
- W2010131696 hasConcept C159877910 @default.
- W2010131696 hasConcept C161584116 @default.
- W2010131696 hasConcept C33923547 @default.
- W2010131696 hasConcept C41008148 @default.
- W2010131696 hasConcept C62354387 @default.
- W2010131696 hasConceptScore W2010131696C105795698 @default.
- W2010131696 hasConceptScore W2010131696C107673813 @default.
- W2010131696 hasConceptScore W2010131696C124101348 @default.
- W2010131696 hasConceptScore W2010131696C134306372 @default.
- W2010131696 hasConceptScore W2010131696C158424031 @default.
- W2010131696 hasConceptScore W2010131696C159877910 @default.
- W2010131696 hasConceptScore W2010131696C161584116 @default.
- W2010131696 hasConceptScore W2010131696C33923547 @default.
- W2010131696 hasConceptScore W2010131696C41008148 @default.
- W2010131696 hasConceptScore W2010131696C62354387 @default.
- W2010131696 hasIssue "2" @default.
- W2010131696 hasLocation W20101316961 @default.
- W2010131696 hasOpenAccess W2010131696 @default.
- W2010131696 hasPrimaryLocation W20101316961 @default.
- W2010131696 hasRelatedWork W2026488516 @default.
- W2010131696 hasRelatedWork W2028868645 @default.
- W2010131696 hasRelatedWork W2055508990 @default.
- W2010131696 hasRelatedWork W2117957819 @default.
- W2010131696 hasRelatedWork W2141232370 @default.
- W2010131696 hasRelatedWork W2166661714 @default.
- W2010131696 hasRelatedWork W2522150281 @default.
- W2010131696 hasRelatedWork W3122327838 @default.
- W2010131696 hasRelatedWork W4304809013 @default.
- W2010131696 hasRelatedWork W2183380562 @default.
- W2010131696 hasVolume "2" @default.
- W2010131696 isParatext "false" @default.
- W2010131696 isRetracted "false" @default.
- W2010131696 magId "2010131696" @default.
- W2010131696 workType "article" @default.