Talk
The Use of Panel Data Models for Ageing Living Individuals from Longitudinal Data of Dental and Skeletal Maturation
Andrade, M. A. P. (Andrade, M. A. P.); Hugo C. Violante Cardoso (Cardoso, H. C. V.);
Event Title
Proccedings da International Work-Conference Time Series Analysis – ITISE 2014
Year (definitive publication)
2014
Language
English
Country
Spain
More Information
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Abstract
The current need in the forensic community to provide accurate age estimates for living individuals has stimulated the testing and development of new approaches. The current available 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 nal 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. The study wishes to assess which of the possible panel data models is more appropriate and which variables perform best in these models. The use of the random-effects models is discussed as it was proven to be the correct choice for the problem under study. While determining the combination of variables that best provides an estimate of age in young males around 16 years, only two were selected. The quality of the model with the best results is evaluated by how much variability explained is lost when the number of variables is reduced. The critical variables in the model used to estimate the age of juveniles, were fusion of the ulna and formation of the third molar. In contrast, fusion of the radius and formation of the second molar were much less important in the model. When dental and skeletal maturation is used in the combined the score version, the results show that the models are not improved.
Acknowledgements
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Keywords
Age estimation, Forensic diagnosis, Panel data