A Bayesian approach to the estimation of the age of humans from tooth development and wear

Examination of dental development is considered to be an accurate method of ageing non-adults, but ageing adults from dental wear is much less accurate. Miles’ method is generally accepted to be the best way we have to derive estimates of tooth-wear ages because it takes into account population variability in wear-rates. Here we develop a Bayesian approach to ageing from dental development and tooth-wear, using a latent trait model and logistic regression to estimate the ages of individuals whose tooth development and/or wear has been scored on ordinal scales. In addition to the original methods this: (a) accounts for uncertainties in tooth development; (b) incorporates in a natural fashion individuals with teeth missing post-mortem. Numerical integrations were performed using Markov-Chain Monte-Carlo techniques and WinBUGS software