Human Biology Open Access Pre-Prints
Document Type
Article
Anticipated Volume
93
Anticipated Issue
1
Abstract
Dental development has been used to assess whether an individual may be below or above an age that serves as a legal threshold. In this paper we use development of the first and second mandibular molars from a large sample of individuals (N=2,666) to examine the age threshold for minimum age of criminal responsibility. We apply a bivariate ordered probit model to dental scores following the Moorrees et al. (1963) system with the addition of a crypt absent/crypt present stage. We then use a ten-fold cross-validation within each of the sexes to show that the bivariate models produce unbiased estimates of age, but that they are heteroscedastic (with increasing spread of the estimates against actual age). To address the age threshold problem, we assume a normal prior centered on the threshold. We then integrate the product of the prior and the likelihood up to the age threshold and again starting at the age threshold. The ratio of these two integrals is a Bayes' factor, and because the prior is symmetric around the threshold, the Bayes' factor also can be interpreted as the posterior odds that an individual is over the age threshold versus under the age threshold. We found it 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 are the first two molars, the question of dental evidence regarding the age of majority (generally 18 years) remains problematic.
Recommended Citation
Konigsberg, Lyle W.; Frankenberg, Susan R.; Sgheiza, Valerie; and Liversidge, Helen M., "Prior Probabilities and the Age Threshold Problem: First and Second Molar Development" (2021). Human Biology Open Access Pre-Prints. 186.
https://digitalcommons.wayne.edu/humbiol_preprints/186