Optimal trait scoring for age estimation.

OBJECTIVES

Little attention has been paid to questions about the applicability of parametric models to age estimation data and the related problem of how to adjust trait scoring in light of potential deviations from particular parametric models. This article addresses this deficit.

METHODS

A Lagrange multiplier goodness-of-fit test is applied to two datasets to address the question of whether or not attainment ages for stages are log-normally distributed. The first dataset used in this article consists of scores of the Todd ten-phase system for the pubic symphysis obtained from 938 individuals with known ages. The second dataset consists of scores for 15 stages of formation for the second mandibular molar scored in 2,304 individuals of known age.

RESULTS

For the Todd ten-phase system there is a significant departure from log-normally distributed ages of attainment. To obtain an acceptable goodness-of-fit statistic, Todd scores consequently are collapsed into an eight-phase system that maintains scores I through VII as individual scores but combines phases VIII through X into one phase. The 15-stage scoring system for the second mandibular molar has an acceptable fit to the log-normal distribution for ages of attainment.

CONCLUSIONS

The results from the analysis of the Todd pubic symphysis scores show that researchers should use goodness-of-fit tests for parametric models before deciding to collapse scores. Further, such goodness-of-fit tests are an essential tool in answering questions concerning the suitability of various parametric models. For the 15-stage scoring of the second mandibular molar, the log-normal model is appropriate for attainment ages.