The Utility of Cranial and Dental Data in an Integrated Approach to Population Affinity

dc.contributor.advisorSpradley, M. Kate
dc.contributor.authorSiegert, Courtney C.
dc.contributor.committeeMemberHerrmann, Nicholas P.
dc.contributor.committeeMemberTaylor, Nicole L.
dc.contributor.committeeMemberHefner, Joseph T.
dc.contributor.committeeMemberBlue, Sarah A.
dc.description.abstractCranial and dental skeletal data have been used by biological anthropologists to better understand human variation at local, regional, and global scales. While preservation of remains may dictate the availability of data, it is often researcher preference that determines the specific data type is used, typically independent of one another. However, it is unclear to what extent these data types reflect similar population structures. This knowledge gap is significant considering most researchers treat these data types as interchangeable when exploring population relationships and estimating group membership in an applied context. As forensic anthropologists shift from broad estimates of ancestry to the estimation of population affinity and geographic origin, research indicates the combination of multiple skeletally derived data types improves correct classification among closely related groups. Therefore, by assessing the utility of a multifactor and integrated approach to estimating population affinity, the following research sought to treat the skull of modern human populations as an integrated biological unit, while considering the potential impact to forensic methodology. Craniometrics, cranial non-metrics, dental metrics, and dental morphology data were collected from skeletal material representing American Black (n=15), American White (n=140), and Latin American Migrant (n=178) populations. Data were analyzed using latent class analysis, a type of finite mixture modeling used to identify unobserved subgroups or classes within a population. This type of mixture model assumes that within the heterogeneous data, there is a set of unobserved, or latent, variables whose pattern can predict class membership. Results indicate the combination of multiple data types into a unified model consistently identified four and five latent classes or groups within the sample population. This suggests that an integrated approach to understanding human variation has utility in forensic anthropology. By accounting for more within-group variation, this combined approach adds to a growing body of work that indicates skeletally derived data can provide fine-grained group membership estimates (i.e., population affinity), beyond the broad, continental origins associated with ancestry estimation.
dc.format.extent138 pages
dc.format.medium1 file (.pdf)
dc.identifier.citationSiegert, C. C. (2023). The utility of cranial and dental data in an integrated approach to population affinity (Unpublished dissertation). Texas State University, San Marcos, Texas.
dc.subjecthuman variation
dc.subjectpopulation affinity
dc.subjectLatin American migrants
dc.titleThe Utility of Cranial and Dental Data in an Integrated Approach to Population Affinity
dc.typeDissertation State University of Philosophy


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