{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T14:55:06Z","timestamp":1786978506461,"version":"build-2736575974"},"reference-count":37,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2025,4,11]],"date-time":"2025-04-11T00:00:00Z","timestamp":1744329600000},"content-version":"vor","delay-in-days":12,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000066","name":"National Institute of Environmental Health Sciences","doi-asserted-by":"publisher","award":["P30ES007048"],"award-info":[{"award-number":["P30ES007048"]}],"id":[{"id":"10.13039\/100000066","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000066","name":"National Institute of Environmental Health Sciences","doi-asserted-by":"publisher","award":["R01ES029963"],"award-info":[{"award-number":["R01ES029963"]}],"id":[{"id":"10.13039\/100000066","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000066","name":"National Institute of Environmental Health Sciences","doi-asserted-by":"publisher","award":["R56ES028121"],"award-info":[{"award-number":["R56ES028121"]}],"id":[{"id":"10.13039\/100000066","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000066","name":"National Institute of Environmental Health Sciences","doi-asserted-by":"publisher","award":["T32ES013678"],"award-info":[{"award-number":["T32ES013678"]}],"id":[{"id":"10.13039\/100000066","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000139","name":"U.S. Environmental Protection Agency","doi-asserted-by":"publisher","award":["RD\u20108358720"],"award-info":[{"award-number":["RD\u20108358720"]}],"id":[{"id":"10.13039\/100000139","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Statistics in Medicine"],"published-print":{"date-parts":[[2025,3,30]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>As individuals are exposed to a myriad of potentially harmful pollutants every day, it is important to determine which actors have the greatest influence on health outcomes. However, jointly modeling the associations of multiple pollutant exposures is often hindered by the presence of highly correlated chemicals originating from a common source. A popular approach to analyzing associations between a disease outcome and several highly correlated exposures is Weighted Quantile Sum Regression (WQSR) modeling. WQSR provides increased stability in estimating model parameters but requires data splitting to estimate individual and group effects of chemicals, which reduces the power of the approach. A recent Bayesian implementation of WQSR regression provides a model fitting procedure that avoids data splitting at the cost of high computational expense on large data. In this paper, we introduce a Frequentist Grouped Weighted Quantile Sum Regression (FGWQSR) model that can be fitted efficiently to large datasets without requiring data splitting. FGWQSR produces estimates of the joint effect of mixture groups and of individual chemicals, and likelihood\u2010ratio\u2010based tests that account for FGWQSR's non\u2010standard asymptotics. We demonstrate that FGWQSR is well calibrated for type\u2010I errors while outperforming both Bayesian Grouped Weighted Quantile Sum Regression and Quantile Logistic Regression in terms of statistical power to detect the effects of mixture groups and individual chemicals. In addition, we show that FGWQSR is robust to model misspecification and can be fitted on large datasets in a fraction of the time required for BGWQSR. We apply FGWQSR to a dataset of 317\u2009767 mother\u2010child pairs with exposure profiles generated by chemical transport models to study the associations between several components found in particulate matter with an aerodynamic diameter smaller than 2.5  (PM) and child Autism Spectrum Disorder (ASD) diagnosis before age 5. PM copper and PM crustal material are found to be statistically significantly associated with ASD diagnosis by five years of age.<\/jats:p>","DOI":"10.1002\/sim.70078","type":"journal-article","created":{"date-parts":[[2025,4,11]],"date-time":"2025-04-11T06:52:51Z","timestamp":1744354371000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Frequentist Grouped Weighted Quantile Sum Regression for Correlated Chemical Mixtures"],"prefix":"10.1002","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0508-4552","authenticated-orcid":false,"given":"Daniel","family":"Rud","sequence":"first","affiliation":[{"name":"Department of Population and Public Health Sciences University of Southern California  Los Angeles CA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Md","family":"Mostafijur Rahman","sequence":"additional","affiliation":[{"name":"Department of Population and Public Health Sciences University of Southern California  Los Angeles CA USA"},{"name":"Department of Environmental Health Sciences Tulane University School of Public Health and Tropical Medicine  New Orleans LA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anny H.","family":"Xiang","sequence":"additional","affiliation":[{"name":"Department of Research &amp; Evaluation Kaiser Permanente Southern California  Pasadena CA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rob","family":"McConnell","sequence":"additional","affiliation":[{"name":"Department of Population and Public Health Sciences University of Southern California  Los Angeles CA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fred","family":"Lurmann","sequence":"additional","affiliation":[{"name":"Sonoma Technology, Inc.  Petaluma CA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael J.","family":"Kleeman","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering University of California  Davis CA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joel","family":"Schwartz","sequence":"additional","affiliation":[{"name":"Department of Environmental Health and Epidemiology Harvard T.H. Chan School of Public Health  Boston MA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhanghua","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Population and Public Health Sciences University of Southern California  Los Angeles CA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sandy","family":"Eckel","sequence":"additional","affiliation":[{"name":"Department of Population and Public Health Sciences University of Southern California  Los Angeles CA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juan","family":"Pablo Lewinger","sequence":"additional","affiliation":[{"name":"Department of Population and Public Health Sciences University of Southern California  Los Angeles CA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,4,11]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1289\/ehp.02110s125"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph8030629"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1097\/01.ede.0000164811.25760.f1"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1177\/2042018819897046"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1289\/ehp.1408630"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41366\u2010021\u201000783\u20109"},{"issue":"76","key":"e_1_2_10_8_1","article-title":"An Overview of Methods to Address Distinct Research Questions on Environmental Mixtures: An Application to Persistent Organic Pollutants and Leukocyte Telomere Length","volume":"18","author":"Gibson E. 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