<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Gu Y</submitter><funding>NIDCR NIH HHS</funding><pagination>551-572</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC8963777</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>16(1)</volume><pubmed_abstract>Community water fluoridation is an important component of oral health promotion, as fluoride exposure is a well-documented dental caries-preventive agent. Direct measurements of domestic water fluoride content provide valuable information regarding individuals' fluoride exposure and thus caries risk; however, they are logistically challenging to carry out at a large scale in oral health research. This article describes the development and evaluation of a novel method for the imputation of missing domestic water fluoride concentration data informed by spatial autocorrelation. The context is a state-wide epidemiologic study of pediatric oral health in North Carolina, where domestic water fluoride concentration information was missing for approximately 75% of study participants with clinical </pubmed_abstract><journal>The annals of applied statistics</journal><pubmed_title>PARTITIONING AROUND MEDOIDS CLUSTERING AND RANDOM FOREST CLASSIFICATION FOR GIS-INFORMED IMPUTATION OF FLUORIDE CONCENTRATION DATA.</pubmed_title><pmcid>PMC8963777</pmcid><funding_grant_id>U01 DE025046</funding_grant_id><pubmed_authors>Shah M</pubmed_authors><pubmed_authors>Ginnis J</pubmed_authors><pubmed_authors>Divaris K</pubmed_authors><pubmed_authors>Preisser JS</pubmed_authors><pubmed_authors>Gu Y</pubmed_authors><pubmed_authors>Simancas-Pallares MA</pubmed_authors><pubmed_authors>Shrestha P</pubmed_authors><pubmed_authors>Zeng D</pubmed_authors></additional><is_claimable>false</is_claimable><name>PARTITIONING AROUND MEDOIDS CLUSTERING AND RANDOM FOREST CLASSIFICATION FOR GIS-INFORMED IMPUTATION OF FLUORIDE CONCENTRATION DATA.</name><description>Community water fluoridation is an important component of oral health promotion, as fluoride exposure is a well-documented dental caries-preventive agent. Direct measurements of domestic water fluoride content provide valuable information regarding individuals' fluoride exposure and thus caries risk; however, they are logistically challenging to carry out at a large scale in oral health research. This article describes the development and evaluation of a novel method for the imputation of missing domestic water fluoride concentration data informed by spatial autocorrelation. The context is a state-wide epidemiologic study of pediatric oral health in North Carolina, where domestic water fluoride concentration information was missing for approximately 75% of study participants with clinical </description><dates><release>2022-01-01T00:00:00Z</release><publication>2022 Mar</publication><modification>2025-04-19T00:40:59.562Z</modification><creation>2025-04-07T11:45:03.826Z</creation></dates><accession>S-EPMC8963777</accession><cross_references><pubmed>35356492</pubmed><doi>10.1214/21-aoas1516</doi></cross_references></HashMap>