Graduation Year


Document Type




Degree Name

Master of Arts (M.A.)

Degree Granting Department


Major Professor

Erin H. Kimmerle, Ph.D.

Committee Member

Christian E. Wells, Ph.D.

Committee Member

Jonathan Bethard, Ph.D.


3D-ID, Craniometrics, Fordisc 3.1, Geographic Ancestry, Population Affiliation


Research on current methods of ancestral estimation must reflect on biological heritage to aid in human identification. Using modern craniometrics methods, how do individuals with a varied biological history affect ancestral estimation? Today, the most used and reliable methods for craniometrics analysis for ancestral estimation in forensic anthropology are computer programs. Two programs are analyzed in this study, Fordisc 3.0 and 3D-ID. The analysis of these computer programs goes beyond the controlled environment provided by an osteological collection. These remains of individuals were unidentified, only to be identified later, through academic research, police work, and public outreach. The selection of samples occurred if they fit the following two criteria: 1) To evaluate known ancestry, the victim was initially unidentified but was later positively identified, and 2) both Linear and 3D coordinate craniometric data was available to test Fordisc 3.1 and 3D-ID. Humans adapt to their environment biologically and culturally, identifying with familiar cultures, foods, objects, events and, how we look. Thus, ancestral components to a person’s appearance can help outline the parameters in a search to return a lost loved one to their family and finish the last chapter in an individual’s life. We establish any trends in the correct and incorrect estimations by analyzing the posterior probability (pp) and typicalities (typ). Both computer programs struggled with the “Hispanic” cohort placement while finding higher reliability in European Americans’ estimations than any other ancestral group for both 3D-ID and Fordisc 3.1.

Included in

Biology Commons