Aeging living individuals from logitudinal data of dental and skeletal maturation: a first attempt

• Autor(a) principal: Andrade, M.
• Data de Publicação: 2015
• Outros Autores: Cardoso, H. C. V.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10071/10643
• topic: Age estimation; Panel data; Fixed effects; Random effects

The current need in the forensic community to provide accurate age estimates for living individuals stimulates the testing and development of new approaches. The purposed guidelines suggest that a dental and skeletal age estimate should be provided, but the expert usually has to rely on two estimates obtained from different methods that cannot be combined, and the final judgment is based on a more subjective assessment of which age is more reliable or how the two estimates can be combined. The purpose of this study is to discuss the use of panel data models to develop age estimation methods that rely on a combination of dental and skeletal maturation in a longitudinal sample of French-Canadian children between the ages of 7 and 15 years old, for legal purposes. It is intended to find out if some conjectures about possible models are true and which variables are more important in the models that perform well. It is presented and discussed the use of random-effects models which was proven to be the correct choice for the problem in study. In the search for the best combination of variables that allows to obtain a model to estimate the age young males around 16 years two were selected. For the model with better results it is evaluated how much percentage of variability explained is lost when the number of variables is reduced. In what concerns the determinant variables in the model to estimate the age of juveniles, for the bones variables it was demonstrated that ulna is fundamental in the model as opposed to radius, which proved to be much less important. Equivalently, the third molar is a primacy variable to consider in any model for the age estimation. For the score index variables the results are either much inferior to the chosen models or, surprisingly, without any interest.