An inter- and intra-observer test of the computer program CRANID. (August 2022)

• Record Type: Journal Article
• Authors: Lee, Matthew; Gerdau-Radonic, Karina
• Is Part Of: Forensic science international. Volume 337(2022)
• Publication Date: 2022-08
• Subjects: Craniometrics -- Ancestry estimation -- CRANID -- Inter-observer effects -- Intra-observer effects; Medical jurisprudence -- Periodicals; Chemistry, Forensic -- Periodicals; Forensic Medicine -- Periodicals; Médecine légale -- Périodiques; Chimie légale -- Périodiques; Gerechtelijke geneeskunde; Gerechtelijke chemie; Gerechtelijke psychiatrie; Chemistry, Forensic; Medical jurisprudence; Electronic journals; Periodicals; Electronic journals; 614.1
• DOI: 10.1016/j.forsciint.2022.111375
• Languages: English
• ISSNs: 0379-0738

Abstract

Abstract: The use of cranial analysis, through metric and/or morphological data, remains a popular method within biological anthropology and its subfields to allow for the analysis of an individual. These methods increasingly use multivariate statistics to empirically measure the degree of similarities between individuals and populations. CRANID is a piece of freeware which allows the user to estimate ancestry from 29 cranial measurements. This paper utilised a previously published dataset (Lee and Gerdau 2020 [29]) of cranial measurements to simulate multiple users estimating the ancestry for a single cranium of known origin. Only 32–68 % of the generated ancestry estimations were found to match the broad geographic region of the tested cranium depending on the statistical test. This paper also highlights aspects of CRANID's results that may make it harder for users to understand the results the program provides. Highlights: Participants' datasets achieved a match to the closest geographic sample of the reference cranium 4.0–28.0 % of the time. Participants' datasets achieved a match to the major geographic region of the reference cranium 32.0–68.0 % of the time. Highlights difficulties in CRANID's results output that make it difficult for users to understand and compare results.