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A New Approach of Juvenile Age Estimation using Measurements of the Ilium and Multivariate Adaptive Regression Splines ( MARS ) Models for Better Age Prediction
Author(s) -
Corron Louise,
Marchal François,
Condemi Silvana,
Chaumoître Kathia,
Adalian Pascal
Publication year - 2017
Publication title -
journal of forensic sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.715
H-Index - 96
eISSN - 1556-4029
pISSN - 0022-1198
DOI - 10.1111/1556-4029.13224
Subject(s) - multivariate adaptive regression splines , mars exploration program , multivariate statistics , forensic anthropology , statistics , regression analysis , regression , nonparametric regression , consistency (knowledge bases) , bivariate analysis , nonparametric statistics , sample size determination , computer science , mathematics , geography , artificial intelligence , biology , archaeology , astrobiology
Juvenile age estimation methods used in forensic anthropology generally lack methodological consistency and/or statistical validity. Considering this, a standard approach using nonparametric Multivariate Adaptive Regression Splines ( MARS ) models were tested to predict age from iliac biometric variables of male and female juveniles from Marseilles, France, aged 0–12 years. Models using unidimensional (length and width) and bidimensional iliac data (module and surface) were constructed on a training sample of 176 individuals and validated on an independent test sample of 68 individuals. Results show that MARS prediction models using iliac width, module and area give overall better and statistically valid age estimates. These models integrate punctual nonlinearities of the relationship between age and osteometric variables. By constructing valid prediction intervals whose size increases with age, MARS models take into account the normal increase of individual variability. MARS models can qualify as a practical and standardized approach for juvenile age estimation.