Application of the Optimized Summed Scored Attributes Method to Sex Estimation in Asian Crania

The optimized summed scored attributes (OSSA) method was recently introduced and validated for nonmetric ancestry estimation between American Black and White individuals. The method proceeds by scoring, dichotomizing, and subsequently summing ordinal morphoscopic trait scores to maximize between‐group differences. This study tests the applicability of the OSSA method for sex estimation using five cranial traits given the methodological similarities between classifying sex and ancestry. A large sample of documented crania from Japan and Thailand (n = 744 males, 320 females) are used to develop a heuristically selected OSSA sectioning point of ≤1 separating males and females. This sectioning point is validated using a holdout sample of Japanese, Thai, and Filipino (n = 178 males, 82 females) individuals. The results indicate a general correct classification rate of 82% using all five traits, and 81% when excluding the mental eminence. Designating an OSSA score of 2 as indeterminate is recommended.     

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 Optimized Summed Scored Attributes Method for the Classification of U.S. Blacks and Whites: A Validation Study

Recently, Hefner and Ousley (2014) introduced the optimized summed scored attributes (OSSA) method that maximizes between‐group differences in U.S. black and white populations by dichotomizing six cranial morphoscopic trait scores. This study tests OSSA using an independent skeletal sample (Hamann‐Todd, n = 208) and positively identified forensic cases (Mercyhurst University, n = 28, and New York City Office of Chief Medical Examiner, n = 38). An evaluation of trait frequencies suggests shifting the heuristically selected sectioning point separating U.S. black and white populations from ≤ 3 to ≤ 4. We found a total correct classification of 73.0% (B = 50.9%, W = 89.2%) using the originally suggested sectioning point of ≤3, while the total correct classification increases to 79.2% (B = 80.2%, W = 78.5%) with a modified sectioning point of ≤4. With the increased total correct classification and reduced classification bias between ancestry groups, we suggest the modified sectioning point of ≤4 be used when assessing ancestry in forensic unknowns.     

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.     

Morphological Assessment of Ancestry using Cranial Macromorphoscopics,

Ancestry estimation is essential for biological profile estimation in forensic anthropology. Hefner (2009) and Osteoware (Smithsonian Institution, 2011) presented 16 macromorphoscopic traits that can be scored for standardized data collection and can also be used within a statistical framework to estimate ancestry. The primary purpose of this research was to examine the utility of these traits for assessing ancestry. Tests of observer agreement and the range of variation in trait expression were evaluated. A sample of 208 American whites and blacks from the Hamann–Todd Collection were scored, and several classification methods were utilized in accordance with Hefner (2009). Correct classifications for the pooled sex analyses ranged from 73.3% to 86.6% and from 46.7% to 64.3% when the sexes were analyzed independently. Interobserver agreement was variable and was found to be lower than that presented in Hefner (2009). Trait expression was variable in both groups and was generally consistent with Hefner's findings.     

A Test of Sex Estimation in Subadults Using the Elevation of the Auricular Surface from Four Samples of Known Age and Sex

Biological sex is foundational to the work of forensic anthropologists and bioarcheologists. The lack of reliable biological sex estimation methods for subadults has, thus, greatly limited forensic and bioarcheological analyses. Auricular surface elevation showed promise as a subadult sex estimation method in previous studies. This study examined two auricular surface elevation evaluation methods on four subadult samples of known age, sex, and ancestry. Samples were scored as “male,” “female,” or “indeterminate” and results were examined with chi‐square analysis. No consistent sex estimation pattern, accuracy, or predictive value was produced between samples. Only one test was significant using Fisher's exact test analysis (FET = 7.501, p < 0.022): the composite approach on the Hamann‐Todd sample. While age, sample size, or developmental factors may play a role in these results, clearly sample variation does as well. This study found auricular surface elevation was not a useful subadult sex estimation method.     

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.     

Nonmetric Cranial Trait Variation and Ancestry Estimation in Asian and Asian-Derived Groups

Traditionally, precontact Native Americans and Asian groups have been conflated for aspects of the biological profile due to their distantly shared genetic history, although this grouping remains largely unexplored. This study examines craniomorphic variability to ascertain whether Asian groups can be differentiated from each other and from Asian-derived groups using more fine-tuned models. Cranial and mandibular data for 35 nonmetric traits were recorded on precontact Native Americans (n = 150) and modern Japanese (n = 150) and Thai (n = 150) individuals. Chi-square analyses indicate that all groups exhibit statistically significant differences in most traits. Additionally, cross-validated binary logistic regression equations resulted in correct classification rates in the range of 65.0–93.3% and demonstrate that sex does not contribute to statistical models. Therefore, numerous traits provide discriminatory resolution that detects differences between the samples, thus highlighting the potential utility of nonmetric traits in identifying individuals beyond the traditional African, European, and Asian forensic ancestry groupings.     

A Validation Study of the Langley et al. (2017) Decision Tree Model for Sex Estimation

Langley et al. (2017) developed a sex estimation decision tree utilizing two traditional cranial traits (glabella and mastoid) and a new trait: zygomatic extension. This study aimed to test the reliability of their zygomatic extension scoring method and validate their sex estimation method. Ordinal score data were collected from 281 male and female U.S. White and Black individuals. The five traditional cranial traits were collected from physical specimens, while zygomatic extension was scored from 3D cranial models. Intra‐ and interobserver analyses carried out on a subsample of 30 individuals indicate good agreement between zygomatic scores. The decision tree correctly sexed 71.5% of the sample, but a strong sex bias (94.2% correct for females, 49.3% correct for males) severely limits the utility of this method. The Walker (2008) and Stevenson et al. (2009) methods produced higher accuracy rates (80.8% and 82.6%, respectively), although these methods also produced sex and ancestry biases.     

Sex Estimation from Human Cranium: Forensic and Anthropological Interest of Maxillary Sinus Volumes

Sex estimation is a key objective of forensic science. We aimed to establish whether maxillary sinus volumes (MSV) could assist in estimating an individual's sex. One hundred and three CT scans were included. MSV were determined using three‐dimensional reconstructions. Two observers performed three‐dimensional MSV reconstructions using the same methods. Intra‐ and interobserver reproducibility were statistically compared using the intraclass correlation coefficient (ICC) (α = 5%). Both intra‐ and interobserver reproducibility were perfect regarding MSV; both ICCs were 100%. There were no significant differences between right and left MSV (p = 0.083). No correlation was found between age and MSV (p > 0.05). We demonstrated the existence of sexual dimorphism in MSV (p < 0.001) and showed that MSV measurements gave a 68% rate of correct allocations to sex group. MSV measurements could be useful to support sex estimation in forensic medicine.     

A Method for Estimating Sex Using the Clavicle,Humerus, Radius,and Ulna

Sex estimation from skeletal remains can be an important part of preliminary identification. The best source of information for estimating sex is the pelvis but it is not always available for analysis. For these cases, a probabilistic sex estimation method is presented using combinations of standard and alternative measurements of the clavicle, humerus, radius, and ulna. Various equations are developed that are not population specific and that are applicable in various recovery scenarios. The equations were tested using four independent samples (n > 370), including a forensic sample. Allocation accuracies vary by test sample and equation and are consistently good (87.4–97.5%) except for a sample of very small males that show the extreme effects of poverty and mortality bias. For many of the cases where allocation was incorrect, the probabilistic approach indicated that no confidence should be placed in the incorrect allocation and the unknown should be classified as sex indeterminate.     

A Comparative Assessment of the Chen et al. and Suchey‐Brooks Pubic Aging Methods on a North American Sample, ,

Accurately estimating the age‐at‐death of adult human skeletons is fundamental in forensic anthropology. This study evaluates the accuracy of two pubic bone age estimation methods—Chen et al. and Suchey‐Brooks. Specimens were obtained from a known collection of modern pubic bones curated at the Maricopa County Forensic Science Center in Phoenix, Arizona. A sample of 296 left male pubic bones of European ancestry was statistically evaluated via bias, absolute mean error, and intra‐ and inter‐observer error. Results indicate that the two methods are similar; the Suchey‐Brooks method is the most accurate for aging young adults (error c. 7 years), while the Revised Chen et al. method is most accurate for aging middle‐age adults (error c. 6 years). Thus, the Chen et al. method is an important contribution to forensic anthropology for aging older adult skeletal remains. There are, however, some limitations such as subjectivity and the intricate scoring system of Chen et al. method.     

Discrete Traits of the Sternum and Ribs: A Useful Contribution to Identification in Forensic Anthropology and Medicine

During forensic anthropological investigation, biological profile is determined by age, sex, ancestry, and stature. However, several individuals may share the same profile. Observation of discrete traits can yield useful information and contribute to identification. This research establishes the frequency of discrete traits of the sternum and ribs in a modern population in southern France, using 500 computer tomography (CT) scans of individuals aged 15–60 years. Only discrete traits with a frequency lower than 10% according to the literature were considered, a total of eight traits. All scans examined were three‐dimensional (3D) volume renderings from DICOM images. In our population, the frequency of all the discrete traits was lower than 5%. None were associated with sex or age, with the exception of a single trait, the end of the xiphoid process. Our findings can usefully be applied for identification purposes in forensic anthropology and medicine.     

Examining Interobserver Reliability of Metric and Morphoscopic Characteristics of the Mandible

Mandibular metric and morphological characteristics have long been used for sex and ancestry estimation. Currently, there are no large‐scale studies examining interobserver agreement, particularly examining the role of observer experience. This study examines the interobserver agreement of six morphoscopic and eleven metric mandibular variables. Four observers with varied levels of experience scored 183 mandibles from the William M. Bass Donated Skeletal Collection. Absolute agreement and consistency were evaluated with the intraclass correlation coefficient (ICC). Additionally, technical error of measurement (TEM) and relative TEM (%TEM) were calculated for each metric variable. All analyses were conducted twice—once with all observers and again with only experienced observers. Results show mean morphoscopic agreement of 0.543 among all observers and 0.615 for experienced observers, and mean metric agreement of 0.886 among all observers and 0.911 for experienced observers. Further, no TEM exceeded 2 mm. All results were significant (p < 0.001).     

Secular Change in Morphological Pelvic Traits used for Sex Estimation

This research evaluates secular change in Phenice's (Am J Phys Anthropol, 30, 1969 and 297) three morphological traits of the pubis, as described by Klales et al. (Am J Phys Anthropol, 149, 2012 and 104): medial aspect of the ischio‐pubic ramus, subpubic contour, and ventral arc. Ordinal scores were collected for these traits and compared between a sample of innominates from the historical Hamann–Todd Collection (n = 170) and modern Bass Donated Collection (n = 129). Using the Freeman–Halton test, significant differences between temporal sample score frequencies were found for all traits in females and for the subpubic contour and ventral arc in males. Despite these findings, classification accuracy using logistic regression between the temporal periods remained low (68.7%). These results suggest that secular changes in trait expression are occurring; however, sex estimation methods using these traits and created with historical samples are still applicable to modern forensic cases. In fact, the secular changes occurring in these traits contribute to better classification accuracy between sexes in modern populations.     

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.     

Introducing Human Mandible Identification [(hu)MANid]: A Free,Web‐Based GUI to Classify Human Mandibles

Statistical programs have revolutionized the way in which forensic anthropologists conduct casework by allowing practitioners to use computationally complex analytics at the click of a button. Importantly, the products of these statistical programs are reproducible and contain measures of error or uncertainty, thereby strengthening conclusions. This paper is an introduction to (hu)MANid, a free, web‐based application that uses linear and mixture discriminant function analyses to classify human mandibles into one of many worldwide and/or periodic reference groups. The mechanics, development, and use of the application will be discussed. Further, the program was tested against other software to compare model performances and classifications. Total correct classifications among the test cases and programs were identical. Ten mandibles were tested using both statistical procedures. Mixture discriminant analysis improved classification by an average of 9.3% and correctly identified three more mandibles than LDA. Therefore, we believe (hu)MANid will be an asset to the anthropological community.     

Forensic Applicability of Femur Subtrochanteric Shape to Ancestry Assessment in Thai and White American Males

Ancestry assessment from the postcranial skeleton presents a significant challenge to forensic anthropologists. However, metric dimensions of the femur subtrochanteric region are believed to distinguish between individuals of Asian and non‐Asian descent. This study tests the discriminatory power of subtrochanteric shape using modern samples of 128 Thai and 77 White American males. Results indicate that the samples' platymeric index distributions are significantly different (p ≤ 0.001), with the Thai platymeric index range generally lower and the White American range generally higher. While the application of ancestry assessment methods developed from Native American subtrochanteric data results in low correct classification rates for the Thai sample (50.8–57.8%), adapting these methods to the current samples leads to better classification. The Thai data may be more useful in forensic analysis than previously published subtrochanteric data derived from Native American samples. Adapting methods to include appropriate geographic and contemporaneous populations increases the accuracy of femur subtrochanteric ancestry methods.     

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.