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Data for validation of osteometric methods in forensic anthropology. | LitMetric

Data for validation of osteometric methods in forensic anthropology.

Data Brief

Department of Anthropology, University of Tennessee, 502 Strong Hall, 1621 Cumberland Ave., Knoxville, TN 37996, USA.

Published: August 2018

Many techniques in forensic anthropology employ osteometric data, although little work has been done to investigate the intrinsic error in these measurements. These data were collected to quantify the reliability of osteometric data used in forensic anthropology research and case analyses. Osteometric data (n = 99 measurements) were collected on a random sample of William M. Bass Donated Collection skeletons (n = 50 skeletons). Four observers measured the left elements of 50 skeletons. After the complete dataset of 99 measurements was collected on each of the 50 skeletons, each observer repeated the process for a total of four rounds. The raw data is available on Mendeley Data ( ). An example of the data analyses performed to evaluate and quantify observer error is provided for the variable GOL (maximum cranial length); these analyses were performed on each of the 99 measurements. Two-way mixed ANOVAs and repeated measures ANOVAs with pairwise comparisons were run to examine intraobserver and interobserver error, and relative and absolute technical error of measurement (TEM) was calculated to quantify the observer variation. This data analysis supported the dissemination of a free laboratory manual of revised osteometric definitions ([1], pdf available at https://fac.utk.edu/wp-content/uploads/2016/03/DCP20_webversion.pdf) and an accompanying instructional video (https://www.youtube.com/watch?v=BtkLFl3vim4). This manual is versioned and updatable as new information becomes available. Similar validations of scientific data used in forensic methods would support the ongoing effort to establish valid and reliable methods and protocols for proficiency testing, training, and certification.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5992973PMC
http://dx.doi.org/10.1016/j.dib.2018.04.148DOI Listing

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