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Quantile regression for mixed models with an application to examine blood pressure trends in China

UNC Libraries(2020)10.17615/8jmf-rv64Source: DataRank Database

Quantile regression for mixed models with an application to examine blood pressure trends in China is a research paper published in UNC Libraries (2020). On theSindex it has a DataRank of 0.

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (4 grants)Impact (FWCI 0.00)OA: greenTopics (20)IDs (PubMed, OpenAlex)SDGs (2)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (4)

Luke B. Smith,Montserrat Fuentes,Penny Gordon-Larsen ORCID,Brian J. Reich ORCID

Live enrichment

PubMed:19965766 OpenAlex:https://openalex.org/W4297962663

National Institutes of Health

Grant: 5R01HD030880-12

Monitoring Social Change: Health, Reproduction, Aging

National Institutes of Health

Grant: 5R01ES014843-06

Space-time Modeling for Linking Climate Change,Pollutant Exposure, Built Environm

National Institutes of Health

Grant: 5R01HL108427-03

Emergence of Cardiometabolic Risk Across the Lifecycle in China

National Institutes of Health

Grant: 3R24HD050924-05S1

Carolina Population Center

FWCI

0.00

Citation Percentile

0.2%

greenLicense: arXiv Non-Exclusive Distribution

repositoryhttps://doi.org/10.17615/8jmf-rv64

https://doi.org/10.1214/15-aoas841

https://dx.doi.org/10.48550/arxiv.1511.01641

https://dx.doi.org/10.17615/8jmf-rv64

https://pubmed.ncbi.nlm.nih.gov/28066516

Fields of Study

Statistical Methods in Epidemiology01 natural sciences0101 mathematics

Keywords

Quantile regressionChinaEconometricsQuantileRegression analysisStatisticsGeographyMathematicsFOS: Computer and information scienceslongitudinalblood pressureBayesianStatistics - ApplicationsApplications of statistics to biology and medical sciences; meta analysismultivariateApplications (stat.AP)Nonparametric regression and quantile regression

Sustainable Development Goals

SDG 3: 3. Good healthSDG 11: 11. Sustainability