Morphoscopic ancestry estimates in Filipino crania using multivariate probit regression models.

OBJECTIVES: Probit has not been applied to ancestry estimation in forensic anthropology. The goals of this study were to: (1) evaluate the performance of probit analysis as a classification tool for ancestry estimation using ordinal data and (2) expand our current understanding of human cranial variation for an understudied population. METHODS: Multivariate probit models were used to classify the ancestral affiliation of Filipino crania using morphoscopic traits. Ancestral reference populations represented Africa, Asia, and Europe in a three-group model, with the addition of Hispanics in a four-group model. Posterior probabilities across these groups were interpreted as admixture proportions of an individual. Model performance was also evaluated for individuals with missing data. RESULTS: The overall correct classification rates for the three-group and four-group models were 72.1% and 68.6%, respectively. Filipinos classified as Asian 52.9% of the time using three ancestral reference groups and 48.6% using four groups. A large portion of Filipinos also classified as African. There were no significant differences in classification trends or accuracy rates between complete crania and crania with at least one missing variable. CONCLUSIONS: Multivariate probit models using morphoscopic traits perform well when populations are represented in both training and test samples. Probit can also accommodate individuals with missing data. Classifying Filipinos showed only moderate success. Filipinos are more phenotypically similar to Africans than the other Asian samples used here, but still affiliate most closely as Asian. Ancestry methods would benefit from including Filipinos as a reference sample given the additional variation they provide to the continental category of Asian.

Ancestry Estimation Using Cranial and Postcranial Macromorphoscopic Traits.

Ancestry estimation methods using macromorphoscopic (MMS) traits commonly focus exclusively on cranial morphology. The objective of this study was to demonstrate the value of postcranial MMS traits, highlighting a combined cranial/postcranial trait approach to ancestry estimation using quadratic discriminant function and a variety of machine learning classification models including artificial neural networks (aNN), random forest models, and support vector machine. Eight cranial and eleven postcranial MMS traits were collected from the Terry and Bass Skeletal Collections (American Black = 81; American White = 173). Our classification models using cranial and postcranial traits correctly classified 88-92% of the sample, improving classification accuracies by nearly fifteen percent over models relying exclusively on cranial data. These same results demonstrate the importance of a multivariate statistical framework incorporating cranial and postcranial data and the nearly unlimited potential of machine learning models to improve the accuracy of ancestry estimates over traditional methods of analysis. To facilitate implementation in casework, one of the more robust models (aNN) is incorporated into a web-based application, ComboMaMD Analytical, to facilitate cranial and postcranial MMS traits analysis for ancestry estimation.

Observer error and its impact on ancestry estimation using dental morphology.

Dental morphology is becoming increasingly visible in forensic anthropology as part of the estimation of ancestry. As methods are developed based on these data, it is important to understand the role of observer error in data collection and method application. In this study, 10 observers collected dental morphological data on 19 traits on the same set of nine plaques. Various measures of interrater reliability were calculated to assess observer error. Data were then input into one of three ancestry estimation methods based on dental morphology to understand the role of observer error in these methods. Results show low rater reliability for all dental morphological traits when all 10 observers are compared. Rater reliability increases when only experienced observers are compared and traits are dichotomized. Further, differences in trait scores by observers resulted in disparate estimations of ancestry in each of the methods. While observer error appears to be an issue in dental morphological methods of ancestry estimation, these problems can be addressed. An argument is made for advanced training in dental anthropology in laboratories and in graduate programs. Further, methods need to test for and employ traits with high rater agreement.

The macromorphoscopic databank.

The development of identification standards in forensic anthropology requires large and appropriate reference samples comprising individuals with modern birth years. Recent advances in macromorphoscopic trait data collection and analysis have created a need for reference data for classification models and biological distance analyses. The Macromorphoscopic Databank (N ∼ 7,397) serves that function, making publicly available trait scores for a large sample (n = 2,363) of modern American populations and world-wide groups of various geographic origins (n = 1,790). In addition, the MaMD stores reference data for a large sample (n = 3,244) of pre-, proto- and historic Amerindian data, useful for biodistance studies and finer-levels of analysis during NAGPRA-related investigations and repatriations. In developing this database, particular attention was given to the level of classification needed during the estimation of ancestry in a forensic context. To fill the knowledge gap that currently exists in the analysis of these data, the following overview outlines many of the issues and their potential solutions. Developing valuable tools that are useful to other practitioners is the purpose of growing a databank. As the Macromorphoscopic Databank develops through data collection efforts and contributions from the field, its utility as a research and teaching tool will also mature, in turn creating a vital resource for forensic anthropologists for future generations.

Intraobserver Error in Macromorphoscopic Trait Data,.

As part of a much larger investigation into the use of macromorphoscopic trait data by forensic anthropologists to estimate ancestry from unidentified skeletal remains, we conducted a fourteen-year (2002-2016) intraobserver error study. Motivated by the development of a large macromorphoscopic database-which will potentially utilize data collected in 2002-quantification of observer error, the impact of technological improvements in macromorphoscopic trait data collection and observer experience is necessary. To maximize comparisons between the two samples, ten macromorphoscopic traits were assessed. Results revealed three patterns of error relating to observer experience, the introduction of new technologies, and error inherent in the method. Overall, this study found the effect of error on macromorphoscopic trait analysis could be predicted and did not significantly impact their utility.

Application of the Stephan et al. Chest Radiograph Comparison Method to Decomposed Human Remains.

This manuscript describes the use of comparative radiography of the chest to facilitate positive identification of human remains in advanced stages of decomposition. The method reported by Stephan et al. for positive identification of dry, disarticulated skeletal elements was used on semifleshed, decomposing remains. Positive identification was established through multiple points of concordance observed in radiographs of the left and right clavicles and the C5-T1 vertebrae. This case study demonstrates the applicability of the Stephan et al.'s method in cases involving decomposing remains.

Craniofacial Secular Change in Recent Mexican Migrants.

Research by economists suggests that recent Mexican migrants are better educated and have higher socioeconomic status (SES) than previous migrants. Because factors associated with higher SES and improved education can lead to positive secular changes in overall body form, secular changes in the craniofacial complex were analyzed within a recent migrant group from Mexico. The Mexican group represents individuals in the act of migration, not yet influenced by the American environment, and thus can serve as a starting point for future studies of secular change in this population group. The excavation of a historic Hispanic cemetery in Tucson, Arizona, also allows for a comparison between historic Hispanics and recent migrants to explore craniofacial trends over a broad time period, as both groups originate from Mexico. The present research addresses two main questions: (1) Are cranial secular changes evident in recent Mexican migrants? (2) Are historic Hispanics and recent Mexican migrants similar? By studying secular changes within a migrant population group, secular trends may be detected, which will be important for understanding the biological variation of the migrants themselves and will serve as a preliminary investigation of secular change within Mexican migrants. The comparison of a sample of recent Mexican migrants with a historic Hispanic sample, predominantly of Mexican origin, allows us to explore morphological similarities and differences between early and recent Mexicans within the United States. Vault and face size and a total of 82 craniofacial interlandmark distances were used to explore secular changes within the recent Mexican migrants (females, n = 38; males, n = 178) and to explore the morphological similarities between historic Hispanics (females, n = 54; males, n = 58) and recent migrants. Sexes were separated, and multivariate adaptive regression splines and basis splines (quadratic with one knot) were used to assess the direction and magnitude of secular trends for the recent Mexican migrants. Because dates of birth were unavailable for the historic sample, partial least squares discriminant analysis (PLS-DA) was used to evaluate morphological differences between historic and recent Mexican migrant samples. The data were separated into a training data set and a testing data set to ensure realistic results. Males had eight variables (four positive and four negative) and females had six variables (two positive and four negative) that demonstrated significant differences over time. In the PLS-DA, three components were identified as important in model creation and resulted in a classification accuracy of 87% when applied to a testing sample. The high classification accuracy demonstrates significant morphological differences between the two groups, with the historic Hispanic sample displaying overall larger craniofacial dimensions. While differences in cranial morphology are evident between historic Hispanics and recent Mexican migrants, relatively few positive and negative secular trends were detected within the recent migrant sample.

Possible Achondroplastic Dwarf Skull from Montevideo, Uruguay.

Achondroplasia (chondrodystrophia) is an autosomal dominant inherited disorder affecting approximately 1 in 26,000 live births and is the most common cause of dwarfism in humans. Disproportionate short stature and a suite of craniofacial characteristics typify achondroplasia. The literature available for differential diagnosis of the disorder relies primarily on the postcranial skeleton. In this paper, a possible case of achondroplasia is presented. The cranium presents a unique suite of cranial and craniofacial dysmorphologies. The lack of postcranial remains does not permit their use in the analysis. To make a differential diagnosis and to quantify the observed craniofacial dysmorphologies, craniometric data are compared to modern clinical literature and to craniometric data from known achondroplastic dwarfs. Thin-plate spline analysis is integrated to quantify the differences in degree and magnitude of shape change. This manuscript demonstrates an appropriate methodology for identifying achondroplasia from the cranial skeleton alone.

Macromorphoscopic trait expression in a cranial sample from Medellín, Colombia.

Adjusting existing methods of human identification developed by forensic anthropologists in the United States for use with populations not included in the original development of an analytical method requires data collection using contemporary osteological collections from those populations, and an assessment of the within-group variation present. The primary purpose of this research is to document cranial macromorphoscopic trait variation using methods previously developed in the United States in a sample of 244 individuals from Antioquia, Medellín, Colombia. All individuals are of known age, sex, and birth region. The complex population and demographic history of Colombia makes ancestry assessment particularly difficult in that country. To that end, we explore inter-regional variation throughout Antioquia using birthplace to determine whether forensic anthropologists can provide finer levels of detail beyond identifying an unknown set of human remains as 'Colombian' or, more generally, Hispanic. State and local levels of identification resulting from the varied population histories of each state within Antioquia permit finer resolution, but only to a degree of certainty. Artificial neural networks (aNN) correctly classified only 18.6% of a validation sample, following modest classification accuracies of test/tuning (11.6%) and training (82.8%) samples to original birthplace. As with most neural networks, overfitting is an issue with these analyses. To remedy this overfitting and to document the applicability of aNNs to the assessment of ancestry in Colombia, we pooled the sample of Colombian data and compared that to modern American samples. In those analyses, the best aNN model correctly classified 48.4% (validation) of the sample. Given these results, finer levels of analysis in Colombia are not yet possible using only macromorphoscopic trait data.

Beyond Taphonomy: Exploring Craniometric Variation Among Anatomical Material.

Anatomical crania are occasionally encountered in forensic anthropology laboratories when that material is mistaken for forensically significant human remains. Using craniometric analyses and statistical measures of sample homogeneity, we determine whether anatomical material can be described as a single, homogenous group or as a diverse mix of populations. Twenty-one interlandmark distances were collected from 85 anatomical preparations. Distance measures were calculated between all pairs using a pooled within-sample variance/covariance matrix and then subjected to a Defrise-Gussenhoven test between each paired distance to test whether each pair was drawn randomly from the same population. In the Defrise-Gussenhoven analysis, twenty-two percent (n = 66) of the 300 pairwise combinations were significant at the 0.05 level or below. The level of homogeneity suggests a majority of that material originated from the subcontinent of India or West Asia. Therefore, anatomical material can be viewed as a moderately homogenous group, but with a shared taphonomic history.

Ancestry Estimation Using Macromorphoscopic Traits.

Anthropologists have a lengthy history using cranial nonmetric traits to assess biological distances between populations. These concepts were adopted by forensic anthropologists to estimate ancestry at the individual level using population-based human variation. However, this method of estimation must adhere to the Daubert guidelines to be applied in the modern court system. To that end, a set of cranial macromorphoscopic traits have been proffered to generate a methodological approach to the estimation of ancestry that can be empirically tested and verified. Additionally, various statistical frameworks, parametric and nonparametric, have been employed to calculate error rates and provide probabilistic statements of the strength of these estimations. Recent studies have further advanced the reliability and validity of macromorphoscopic trait analysis through reference datasets, validation studies, and demonstrable exploration of the complex population histories impacting human variation between and within populations worldwide.

The Use of Femoral Neck Axis Length to Estimate Sex and Ancestry.

Having multiple reliable methods of estimating sex and ancestry from various skeletal features increases the likelihood of identifying skeletal remains. Femoral neck axis length (FNAL), as measured in living individuals, has been shown to vary by sex and ancestry. FNAL has not, however, been previously measured directly from skeletonized remains and investigated for its potential use in forensic anthropological applications. This research proposes a method for measuring FNAL from skeletal remains, determines the reliability and repeatability of the measurement, and assesses the validity of FNAL in sex and ancestry estimation. Results showed low interobserver error in the measurement of FNAL (TEM=0.33 mm, R=0.99). Significant differences in FNAL were found between sexes as well as between American Black, American White, and Native American groups. FNAL can correctly classify sex in ~86% of all cases and is considered valuable to sex estimation. The value of FNAL to ancestry estimation, however, is considered limited.

Morphoscopic Trait Expression in "Hispanic" Populations.

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.

The use of tooth crown measurements in the assessment of ancestry.

As the hardest tissue in the body, teeth have the potential to offer a wealth of biological information to the forensic anthropologist, which can include the assessment of ancestry. Using a large data set of dental measurements, the efficacy of mesiodistal and buccolingual tooth dimensions to discriminate between broad, geographically based groups is explored. A general pattern is identified: African populations have the largest teeth, Asians possess teeth of intermediate size, and Europeans have the smallest teeth. In a discriminant function analysis using crown measurements of all teeth (mandibular and maxillary and excluding the third molar), individuals were correctly classified in 71.3% of cases. When the sex of the individual is known, classification is improved up to 88.1% in females and 71.9% of males (cross-validated). Based on these results, we argue that dental metrics can be regularly employed as part of the development of the biological profile.

Statistical classification methods for estimating ancestry using morphoscopic traits.

Ancestry assessments using cranial morphoscopic traits currently rely on subjective trait lists and observer experience rather than empirical support. The trait list approach, which is untested, unverified, and in many respects unrefined, is relied upon because of tradition and subjective experience. Our objective was to examine the utility of frequently cited morphoscopic traits and to explore eleven appropriate and novel methods for classifying an unknown cranium into one of several reference groups. Based on these results, artificial neural networks (aNNs), OSSA, support vector machines, and random forest models showed mean classification accuracies of at least 85%. The aNNs had the highest overall classification rate (87.8%), and random forests show the smallest difference between the highest (90.4%) and lowest (76.5%) classification accuracies. The results of this research demonstrate that morphoscopic traits can be successfully used to assess ancestry without relying only on the experience of the observer.

Ancestry assessment using random forest modeling.

A skeletal assessment of ancestry relies on morphoscopic traits and skeletal measurements. Using a sample of American Black (n = 38), American White (n = 39), and Southwest Hispanics (n = 72), the present study investigates whether these data provide similar biological information and combines both data types into a single classification using a random forest model (RFM). Our results indicate that both data types provide similar information concerning the relationships among population groups. Also, by combining both in an RFM, the correct allocation of ancestry for an unknown cranium increases. The distribution of cross-validated grouped cases correctly classified using discriminant analyses and RFMs ranges between 75.4% (discriminant function analysis, morphoscopic data only) and 89.6% (RFM). Unlike the traditional, experience-based approach using morphoscopic traits, the inclusion of both data types in a single analysis is a quantifiable approach accounting for more variation within and between groups, reducing misclassification rates, and capturing aspects of cranial shape, size, and morphology.

Cranial nonmetric variation and estimating ancestry*.

Historically, when predicting the ancestry of human skeletal remains, forensic anthropologists have not fully considered the variation within human populations, but instead have relied on a typological, experience-based approach. Unfortunately, reliance on observer experience has produced a method that is as much an art as it is a science. This research focuses on the frequency distribution and inter-trait correlations of 11 common morphoscopic traits to demonstrate that the experience-based approach to ancestry prediction is indeed an art that is unscientific, because it is unreplicable, unreliable, and invalid. Ten of 11 traits examined had frequency distributions with significant differences (p < 0.001) between groups, but the range in variation of these traits far exceeds previous assumptions. Such within group variation clearly demonstrates that extreme trait expressions are not reliable for estimating ancestry through visual observation alone, but instead that these traits should be analyzed within a statistical framework.