Reliability for Binary and Ordinal Data in Forensics

dc.contributor.author Arora, Hina
dc.contributor.author Kaplan-Damary, Naomi
dc.contributor.author Stern, Hal
dc.contributor.department Center for Statistics and Applications in Forensic Evidence
dc.date.accessioned 2022-11-08T14:37:34Z
dc.date.available 2022-11-08T14:37:34Z
dc.date.issued 2022-08-08
dc.description.abstract Forensics studies of feature-based comparison decisions typically focus on the accuracy and reliability the decisions. Decisions can be reports in the form of binary conclusions (value / no value) or in the form of ordered categories. In general there is limited covariate information available about either the examiners or the forensic samples being assessed. We propose a methodology to identify groups of examiners that might share decision making abilities or thresholds for decisions. Identifying clusters of examiners can enable us to assess reliability of decisions within these clusters which may be different from the reliability that is evaluated through marginalized data.
dc.description.comments The following poster was presented at the 2022 Joint Statistical Meetings (JSM), Washington, D.C., August 6-11, 2022. Posted with permission of CSAFE.
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/qzXBE3Dv
dc.language.iso en
dc.publisher Copyright 2022, The Authors
dc.subject.disciplines DegreeDisciplines::Social and Behavioral Sciences::Legal Studies::Forensic Science and Technology
dc.title Reliability for Binary and Ordinal Data in Forensics
dc.type Presentation
dspace.entity.type Publication
relation.isOrgUnitOfPublication d8a3c72b-850f-40f6-87c4-8812547080c7
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