json: {"relationships": {"client": {"data": {"type": "clients", "id": "figshare.ars"}}}, "attributes": {"partCount": 0, "contributors": [], "versionCount": 0, "titles": [{"title": "Exploratory Mediation Analysis with Many Potential Mediators"}], "descriptions": [{"descriptionType": "Abstract", "description": "Social and behavioral scientists are increasingly employing technologies such as fMRI, smartphones, and gene sequencing, which yield \u2018high-dimensional\u2019 datasets with more columns than rows. There is increasing interest, but little substantive theory, in the role the variables in these data play in known processes. This necessitates exploratory mediation analysis, for which structural equation modeling is the benchmark method. However, this method cannot perform mediation analysis with more variables than observations. One option is to run a series of univariate mediation models, which incorrectly assumes independence of the mediators. Another option is regularization, but the available implementations may lead to high false-positive rates. In this article, we develop a hybrid approach which uses components of both filter and regularization: the \u2018Coordinate-wise Mediation Filter\u2019. It performs filtering conditional on the other selected mediators. We show through simulation that it improves performance over existing methods. Finally, we provide an empirical example, showing how our method may be used for epigenetic research."}], "referenceCount": 0, "subjects": [{"subject": "Genetics"}, {"subjectScheme": "Fields of Science and Technology (FOS)", "schemeUri": "http://www.oecd.org/science/inno/38235147.pdf", "subject": "FOS: Biological sciences"}, {"subjectScheme": "Fields of Science and Technology (FOS)", "subject": "FOS: Biological sciences"}, {"subject": "Molecular Biology"}, {"subject": "Neuroscience"}, {"subjectScheme": "FOR", "subject": "69999 Biological Sciences not elsewhere classified"}, {"subjectScheme": "FOR", "subject": "19999 Mathematical Sciences not elsewhere classified"}, {"subjectScheme": "Fields of Science and Technology (FOS)", "schemeUri": "http://www.oecd.org/science/inno/38235147.pdf", "subject": "FOS: Mathematics"}, {"subjectScheme": "Fields of Science and Technology (FOS)", "subject": "FOS: Mathematics"}, {"subjectScheme": "FOR", "subject": "111714 Mental Health"}, {"subjectScheme": "Fields of Science and Technology (FOS)", "schemeUri": "http://www.oecd.org/science/inno/38235147.pdf", "subject": "FOS: Health sciences"}, {"subjectScheme": "Fields of Science and Technology (FOS)", "subject": "FOS: Health sciences"}], "container": {}, "state": "findable", "created": "2019-04-11T08:51:19.000Z", "source": "mds", "metadataVersion": 4, "version": null, "isActive": true, "registered": "2019-04-11T08:51:19.000Z", "contentUrl": null, "geoLocations": [], "updated": "2020-08-27T12:51:20.000Z", "fundingReferences": [], "partOfCount": 0, "viewCount": 0, "versionOfCount": 0, "published": "2019", "dates": [{"date": "2019-04-11", "dateType": "Created"}, {"date": "2019-09-18", "dateType": "Updated"}, {"date": "2019", "dateType": "Issued"}], "relatedIdentifiers": [{"relationType": "IsSupplementTo", "relatedIdentifier": "10.1080/10705511.2019.1588124", "relatedIdentifierType": "DOI"}], "reason": null, "rightsList": [{"rightsUri": "https://creativecommons.org/licenses/by/4.0/legalcode", "rightsIdentifier": "cc-by-4.0", "rightsIdentifierScheme": "SPDX", "schemeUri": "https://spdx.org/licenses/", "rights": "Creative Commons Attribution 4.0 International"}], "schemaVersion": "http://datacite.org/schema/kernel-4", "types": {"resourceType": "Dataset", "ris": "DATA", "resourceTypeGeneral": "Dataset", "bibtex": "misc", "citeproc": "dataset", "schemaOrg": "Dataset"}, "publisher": "Taylor & Francis", "publicationYear": 2019, "doi": "10.6084/m9.figshare.7981676", "language": null, "sizes": ["51407 Bytes"], "url": "https://tandf.figshare.com/articles/Exploratory_Mediation_Analysis_with_Many_Potential_Mediators/7981676", "identifiers": [], "citationCount": 0, "formats": [], "downloadCount": 0, "creators": [{"affiliation": [], "nameIdentifiers": [], "name": "Erik-Jan Van Kesteren"}, {"nameType": "Personal", "nameIdentifiers": [], "name": "Oberski, Daniel L.", "familyName": "Oberski", "affiliation": [], "givenName": "Daniel L."}]}, "type": "dois", "id": "10.6084/m9.figshare.7981676", "timestamp": 1598525480}