A Permutation Test-Based Approach to Strengthening Inference on the Effects of Environmental Mixtures: Comparison between Single-Index Analytic Methods.
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| Title: | A Permutation Test-Based Approach to Strengthening Inference on the Effects of Environmental Mixtures: Comparison between Single-Index Analytic Methods. |
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| Authors: | Day, Drew B.1 drew.day@seattlechildrens.org, Sathyanarayana, Sheela1,2,3, LeWinn, Kaja Z.4, Karr, Catherine J.2,3,5, Mason, W. Alex6, Szpiro, Adam A.7 |
| Source: | Environmental Health Perspectives. Aug2022, Vol. 130 Issue 8, p087010-1-087010-9. 9p. 2 Charts, 1 Graph. |
| Subject Terms: | *Pollutants, *Plasticizers, *Environmental exposure, Cognition disorder risk factors, Statistics, Predictive tests, Research evaluation, Confidence intervals, Regression analysis, Prenatal exposure delayed effects, Risk assessment, Child psychopathology, Learning disabilities, Descriptive statistics, Statistical models, Data analysis |
| Abstract: | BACKGROUND: Optimization of mixture analyses is critical to assess potential impacts of human exposures to multiple pollutants. Single-index regression methods quantify total mixture association and chemical component contributions. Single-index methods include several variants of quantile g-computation (QGC) and weighted quantile sum regression (WQSr), though each has limitations. OBJECTIVES: We developed a novel permutation test for WQSr and compared its performance to extant versions of WQSr and QGC in simulation studies and an analysis of prenatal phthalates and childhood cognition. METHODS: WQSr uses ensemble nonlinear optimization to identify weights for mixture exposures in an index associated with the outcome in a prespecified direction, with ensembles based on bootstrap resampling (WQSBS) or random subsetting of exposures (WQSRS). Statistical significance can be assessed without splitting the data (Nosplit), by splitting the data into training and test sets (Split), by repeatedly holding out test sets (RH), or by using a novel permutation test (PT) to obtain a more accurate 푝-value. QGC instead provides a sum mixture coefficient and component coefficients with no constraints on direction. In simulations, we compared false positive rates (FPR) and power to detect true associations and accuracy in estimating mixture weights. We also estimated associations between prenatal phthalate mixtures and childhood IQ in the Conditions Affecting Neurocognitive Development and Learning in Early Childhood cohort using each method. RESULTS: FPR was well controlled at =7% in all but the Nosplit WQSr variants. Among these methods, the WQSBS and WQSRS PT variants had the highest power (89%–98%), with lower power for QGC (85%–93%) and RH (60%–97%) or Split WQSr variants (40%–78%). WQSr methods estimated mixture weights 2–4 times more accurately than the QGC method. Coefficients for mixture associations with full scale IQ varied 3- to 4-fold across analytic methods. DISCUSSION: WQSr paired with our novel permutation test best balanced power and false positive rate when assessing a mixture effect. As new methods develop, each should be examined for performance and applicability. [ABSTRACT FROM AUTHOR] |
| Copyright of Environmental Health Perspectives is the property of National Institute of Environmental Health Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
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| Items | – Name: Title Label: Title Group: Ti Data: A Permutation Test-Based Approach to Strengthening Inference on the Effects of Environmental Mixtures: Comparison between Single-Index Analytic Methods. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Day%2C+Drew+B%2E%22">Day, Drew B.</searchLink><relatesTo>1</relatesTo><i> drew.day@seattlechildrens.org</i><br /><searchLink fieldCode="AR" term="%22Sathyanarayana%2C+Sheela%22">Sathyanarayana, Sheela</searchLink><relatesTo>1,2,3</relatesTo><br /><searchLink fieldCode="AR" term="%22LeWinn%2C+Kaja+Z%2E%22">LeWinn, Kaja Z.</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Karr%2C+Catherine+J%2E%22">Karr, Catherine J.</searchLink><relatesTo>2,3,5</relatesTo><br /><searchLink fieldCode="AR" term="%22Mason%2C+W%2E+Alex%22">Mason, W. Alex</searchLink><relatesTo>6</relatesTo><br /><searchLink fieldCode="AR" term="%22Szpiro%2C+Adam+A%2E%22">Szpiro, Adam A.</searchLink><relatesTo>7</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Environmental+Health+Perspectives%22">Environmental Health Perspectives</searchLink>. Aug2022, Vol. 130 Issue 8, p087010-1-087010-9. 9p. 2 Charts, 1 Graph. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Pollutants%22">Pollutants</searchLink><br />*<searchLink fieldCode="DE" term="%22Plasticizers%22">Plasticizers</searchLink><br />*<searchLink fieldCode="DE" term="%22Environmental+exposure%22">Environmental exposure</searchLink><br /><searchLink fieldCode="DE" term="%22Cognition+disorder+risk+factors%22">Cognition disorder risk factors</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Predictive+tests%22">Predictive tests</searchLink><br /><searchLink fieldCode="DE" term="%22Research+evaluation%22">Research evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Confidence+intervals%22">Confidence intervals</searchLink><br /><searchLink fieldCode="DE" term="%22Regression+analysis%22">Regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Prenatal+exposure+delayed+effects%22">Prenatal exposure delayed effects</searchLink><br /><searchLink fieldCode="DE" term="%22Risk+assessment%22">Risk assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Child+psychopathology%22">Child psychopathology</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+disabilities%22">Learning disabilities</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+models%22">Statistical models</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis%22">Data analysis</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: BACKGROUND: Optimization of mixture analyses is critical to assess potential impacts of human exposures to multiple pollutants. Single-index regression methods quantify total mixture association and chemical component contributions. Single-index methods include several variants of quantile g-computation (QGC) and weighted quantile sum regression (WQSr), though each has limitations. OBJECTIVES: We developed a novel permutation test for WQSr and compared its performance to extant versions of WQSr and QGC in simulation studies and an analysis of prenatal phthalates and childhood cognition. METHODS: WQSr uses ensemble nonlinear optimization to identify weights for mixture exposures in an index associated with the outcome in a prespecified direction, with ensembles based on bootstrap resampling (WQSBS) or random subsetting of exposures (WQSRS). Statistical significance can be assessed without splitting the data (Nosplit), by splitting the data into training and test sets (Split), by repeatedly holding out test sets (RH), or by using a novel permutation test (PT) to obtain a more accurate 푝-value. QGC instead provides a sum mixture coefficient and component coefficients with no constraints on direction. In simulations, we compared false positive rates (FPR) and power to detect true associations and accuracy in estimating mixture weights. We also estimated associations between prenatal phthalate mixtures and childhood IQ in the Conditions Affecting Neurocognitive Development and Learning in Early Childhood cohort using each method. RESULTS: FPR was well controlled at =7% in all but the Nosplit WQSr variants. Among these methods, the WQSBS and WQSRS PT variants had the highest power (89%–98%), with lower power for QGC (85%–93%) and RH (60%–97%) or Split WQSr variants (40%–78%). WQSr methods estimated mixture weights 2–4 times more accurately than the QGC method. Coefficients for mixture associations with full scale IQ varied 3- to 4-fold across analytic methods. DISCUSSION: WQSr paired with our novel permutation test best balanced power and false positive rate when assessing a mixture effect. As new methods develop, each should be examined for performance and applicability. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Environmental Health Perspectives is the property of National Institute of Environmental Health Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1289/EHP10570 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 9 StartPage: 087010-1 Subjects: – SubjectFull: Pollutants Type: general – SubjectFull: Plasticizers Type: general – SubjectFull: Environmental exposure Type: general – SubjectFull: Cognition disorder risk factors Type: general – SubjectFull: Statistics Type: general – SubjectFull: Predictive tests Type: general – SubjectFull: Research evaluation Type: general – SubjectFull: Confidence intervals Type: general – SubjectFull: Regression analysis Type: general – SubjectFull: Prenatal exposure delayed effects Type: general – SubjectFull: Risk assessment Type: general – SubjectFull: Child psychopathology Type: general – SubjectFull: Learning disabilities Type: general – SubjectFull: Descriptive statistics Type: general – SubjectFull: Statistical models Type: general – SubjectFull: Data analysis Type: general Titles: – TitleFull: A Permutation Test-Based Approach to Strengthening Inference on the Effects of Environmental Mixtures: Comparison between Single-Index Analytic Methods. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Day, Drew B. – PersonEntity: Name: NameFull: Sathyanarayana, Sheela – PersonEntity: Name: NameFull: LeWinn, Kaja Z. – PersonEntity: Name: NameFull: Karr, Catherine J. – PersonEntity: Name: NameFull: Mason, W. Alex – PersonEntity: Name: NameFull: Szpiro, Adam A. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: Aug2022 Type: published Y: 2022 Identifiers: – Type: issn-print Value: 00916765 Numbering: – Type: volume Value: 130 – Type: issue Value: 8 Titles: – TitleFull: Environmental Health Perspectives Type: main |
| ResultId | 1 |
