This book chapter assesses the predictive ability of variables, using Pearson correlation coefficients; it discusses the research methodology and findings, which provide empirical support to incorporating conditional dependence into age estimation models and utilizing both continuous and ordinal variables to better capture the developmental states of individuals
Subadult age estimation is dependent on predictable and well-documented biological processes. However, the lack of appropriate contemporary skeletal samples for forensic anthropological methods led to few improvements until advanced imaging offered a means to access large and varied samples. Access to such data enables the substantiation of methodological and theoretical aspects of subadult age estimation. In this chapter, the predictive ability of variables is assessed using Pearson correlation coefficients and the conditional dependence (on age) among variables is quantified using conditional mutual information. Results revealed a clear age dependency to biological processes; neither variable relationships with age nor the mutual information among variables conditioned on age were constant through ontogeny. The findings provide empirical support to incorporating conditional dependence into age estimation models and utilizing both continuous and ordinal variables to better capture the developmental states of individuals. (Published Abstract Provided)
Downloads
Similar Publications
- In-Field Collection and Preservation of Decomposing Human Tissues to Facilitate Rapid Purification and STR Typing
- Pathways to Homelessness: Childhood Maltreatment and Psychiatric Symptoms Increase Risk of Homelessness
- An enhanced computational method for age-at-death estimation based on the pubic symphysis using 3D laser scans and thin plate splines