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Dental development has been used to assess whether an individual may be below or above an age that serves as a legal threshold. This study used development of the first and second mandibular molars from a large sample of individuals (N = 2,676) to examine the age threshold for minimum age of criminal responsibility. A bivariate ordered probit model was applied to dental scores following the Moorrees et al. (1963) system, with the addition of a crypt-absent/present stage. Then a 10-fold cross-validation within each of the sexes showed that the bivariate models produce unbiased estimates of age but are heteroskedastic (with increasing spread of the estimates against actual age). To address the age threshold problem, a normal prior centered on the threshold is assumed, and the product of the prior and the likelihood is integrated up to the age threshold and again starting at the age threshold. The ratio of these two integrals is a Bayes factor, which because the prior is symmetric around the threshold, can also be interpreted as the posterior odds that an individual is over versus under the age threshold. It was necessary to assume an unreasonably high standard deviation of age in the prior to achieve posterior odds that were well above "evens." These results indicate that dental developmental evidence from the first and second molars is of limited use in examining the question of whether an individual is below or over the minimum age of criminal responsibility. As the third molar is more variable in its development than the first two molars, the question of dental evidence regarding the age of majority (generally 18 years) remains problematic.

While discriminant function analysis is an inherently Bayesian method, researchers attempting to estimate ancestry in human skeletal samples often follow discriminant function analysis with the calculation of frequentist-based typicalities for assigning group membership. Such an approach is problematic because it fails to account for admixture and for variation in why individuals may be classified as outliers or nonmembers of particular groups. This article presents an argument and methodology for employing a fully Bayesian approach in discriminant function analysis applied to cases of ancestry estimation. The approach requires adding the calculation, or estimation, of predictive distributions as the final step in ancestry-focused discriminant analyses. The methods for a fully Bayesian multivariate discriminant analysis are illustrated using craniometrics from identified population samples within the Howells published data. The article also presents ways to visualize predictive distributions calculated in more than three dimensions, explains the limitations of typicality measures, and suggests an analytical route for future studies of ancestry and admixture based in discriminant function analysis.

Potential mates analysis is difficult to apply to small historic populations that lack clear boundaries or regular vital event registration. Here I analyze the actual mate pool as an alternative way to identify causes of nonrandom mating when unmarried members are unknown. Factors influencing mate choice within a historic eastern Blue Ridge community in Madison County, Virginia, are examined for four marriage cohorts: 1850-1879, 1880-1899, 1900-1919, and 1920-1939. These factors include nuclear kin avoidance, preferred age differences between mates, and preferences for more distant kin. A simulation is used to recombine members of the cohort-specific pools of married individuals to generate the probabilities of various types of kin marriages. The pedigree and vital statistics data are derived from first-time marriage licenses filled by community members in Madison County from 1794 to 1939. The numbers of marriages examined for each cohort are 88, 120, 132, and 132, respectively; the mate pools constructed from the samples are viewed from the female perspective. The results generated by simulation on the actual mate pools consist of mean kinship coefficients, numbers of marriages between "allowed" kin types, and probabilities of these values when marriage is random with respect to kinship. The results indicate significantly high levels of inbreeding in all four marriage cohorts, primarily because of high levels of first-cousin marriages in the first three cohorts and of first-cousin once-removed marriages in the 1920 cohort. The observed mating patterns are discussed in terms of the social history of the Blue Ridge community and restrictions of the data.