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Richard Hahn","affiliation":[],"nameIdentifiers":[]},{"name":"Murray, Jared S.","nameType":"Personal","givenName":"Jared S.","familyName":"Murray","affiliation":[],"nameIdentifiers":[]},{"name":"Manolopoulou, Ioanna","nameType":"Personal","givenName":"Ioanna","familyName":"Manolopoulou","affiliation":[],"nameIdentifiers":[]}],"titles":[{"title":"A Bayesian Partial Identification Approach to Inferring the Prevalence of Accounting Misconduct"}],"publisher":"Figshare","container":{},"publicationYear":2015,"subjects":[{"subject":"Genetics"},{"subject":"FOS: Biological sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Biological sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Neuroscience"},{"subject":"Pharmacology"},{"subject":"59999 Environmental Sciences not elsewhere classified","subjectScheme":"FOR"},{"subject":"FOS: Earth and related environmental sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Earth and related environmental sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"39999 Chemical Sciences not elsewhere classified","subjectScheme":"FOR"},{"subject":"FOS: Chemical sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Chemical sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"19999 Mathematical Sciences not elsewhere classified","subjectScheme":"FOR"},{"subject":"FOS: Mathematics","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Mathematics","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Cancer"},{"subject":"Science Policy"}],"contributors":[],"dates":[{"date":"2015-12-05","dateType":"Created"},{"date":"2016-05-05","dateType":"Updated"},{"date":"2015","dateType":"Issued"}],"language":null,"types":{"ris":"GEN","bibtex":"misc","citeproc":"article","schemaOrg":"Collection","resourceType":"Collection","resourceTypeGeneral":"Collection"},"relatedIdentifiers":[],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"CC-BY","rightsUri":"http://creativecommons.org/licenses/by/3.0/us"}],"descriptions":[{"description":"This article describes the use of flexible Bayesian regression models for estimating a partially identified probability function. Our approach permits efficient sensitivity analysis concerning the posterior impact of priors on the partially identified component of the regression model. The new methodology is illustrated on an important problem where only partially observed data are available—inferring the prevalence of accounting misconduct among publicly traded U.S. businesses. Supplementary materials for this article are available online.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"xml":"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","url":"https://figshare.com/collections/A_Bayesian_partial_identification_approach_to_infe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