Nonparametric Bayesian Functional Meta-Regression: Applications in Environmental Epidemiology
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yu, Jaeeun | - |
dc.contributor.author | Park, Jinsu | - |
dc.contributor.author | Choi, Taeryon | - |
dc.contributor.author | Hashizume, Masahiro | - |
dc.contributor.author | Kim, Yoonhee | - |
dc.contributor.author | Honda, Yasushi | - |
dc.contributor.author | Chung, Yeonseung | - |
dc.date.accessioned | 2021-08-30T02:52:16Z | - |
dc.date.available | 2021-08-30T02:52:16Z | - |
dc.date.created | 2021-06-19 | - |
dc.date.issued | 2021-03 | - |
dc.identifier.issn | 1085-7117 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/49501 | - |
dc.description.abstract | Two-stage meta-analysis has been popularly used in epidemiological studies to investigate an association between environmental exposure and health response by analyzing time-series data collected from multiple locations. The first stage estimates the location-specific association, while the second stage pools the associations across locations. The second stage often incorporates location-specific predictors (i.e., meta-predictors) to explain the between-location heterogeneity and is called meta-regression. The existing second-stage meta-regression relies on parametric assumptions and does not accommodate functional meta-predictors and spatial dependency. Motivated by these limitations, our research proposes a nonparametric Bayesian meta-regression which relaxes parametric assumptions and incorporates functional meta-predictors and spatial dependency. The proposed meta-regression is formulated by jointly modeling the association parameters and the functional meta-predictors using Dirichlet process (DP) or local DP mixtures. In doing so, the functional meta-predictors are represented parsimoniously by the coefficients of the orthonormal basis. The proposed models were applied to (1) a temperature-mortality association study and (2) suicide seasonality study, and validated through a simulation study. Supplementary materials accompanying this paper appear online. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | SPRINGER | - |
dc.subject | AIR-POLLUTION | - |
dc.subject | MORTALITY | - |
dc.subject | SUNSHINE | - |
dc.subject | SUICIDE | - |
dc.subject | MODELS | - |
dc.subject | HEAT | - |
dc.subject | TEMPERATURE | - |
dc.subject | ADAPTATION | - |
dc.subject | LAG | - |
dc.title | Nonparametric Bayesian Functional Meta-Regression: Applications in Environmental Epidemiology | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Choi, Taeryon | - |
dc.identifier.doi | 10.1007/s13253-020-00409-z | - |
dc.identifier.scopusid | 2-s2.0-85089149631 | - |
dc.identifier.wosid | 000557319400001 | - |
dc.identifier.bibliographicCitation | JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS, v.26, no.1, pp.45 - 70 | - |
dc.relation.isPartOf | JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS | - |
dc.citation.title | JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS | - |
dc.citation.volume | 26 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 45 | - |
dc.citation.endPage | 70 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Life Sciences & Biomedicine - Other Topics | - |
dc.relation.journalResearchArea | Mathematical & Computational Biology | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalWebOfScienceCategory | Biology | - |
dc.relation.journalWebOfScienceCategory | Mathematical & Computational Biology | - |
dc.relation.journalWebOfScienceCategory | Statistics & Probability | - |
dc.subject.keywordPlus | AIR-POLLUTION | - |
dc.subject.keywordPlus | MORTALITY | - |
dc.subject.keywordPlus | SUNSHINE | - |
dc.subject.keywordPlus | SUICIDE | - |
dc.subject.keywordPlus | MODELS | - |
dc.subject.keywordPlus | HEAT | - |
dc.subject.keywordPlus | TEMPERATURE | - |
dc.subject.keywordPlus | ADAPTATION | - |
dc.subject.keywordPlus | LAG | - |
dc.subject.keywordAuthor | Dirichlet process mixture | - |
dc.subject.keywordAuthor | Functional predictor | - |
dc.subject.keywordAuthor | Local Dirichlet process | - |
dc.subject.keywordAuthor | Meta-regression | - |
dc.subject.keywordAuthor | Spatial dependency | - |
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