This study evaluates population variation of eight cranial morphoscopic traits using samples of known southwest Hispanics (n=72), Guatemalans (n=106), American Blacks (n=146), and American Whites (n=218). We applied the support vector machine (SVM) method to build a prediction model based on a subsample (20%) of the data; the remainder of the data was used as a test sample. The SVM approach effectively differentiated between the four groups with correct classification rates between 72% (Guatemalan group) and 94% (American Black group). However, when the Guatemalan and southwest Hispanic samples were pooled, the same model correctly classified all groups with a higher degree of accuracy (American Black=96%; American White=77%; and the pooled Hispanic sample=91%). This study also identified significant differences between the two Hispanic groups in six of the eight traits using univariate statistical tests. These results speak to the unique population histories of these samples and the current use of the term "Hispanic" within forensic anthropology. Finally, we argue that the SVM can be used as a classification model for ancestry estimation in a forensic context and as a diagnostic tool may broaden the application of morphoscopic trait data for the assessment of ancestry.
Keywords: Hispanics; Support Vector Machines; ancestry; forensic anthropology; forensic science; morphoscopic traits.
© 2015 American Academy of Forensic Sciences.