Transition analysis applied to third molar development in a Danish population
| Autor: | Niels Lynnerup, Sara Arge, Jesper L. Boldsen, Palle Holmstrup, Niels Dyrgaard Jensen, Ann Wenzel |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Adult
Male Generalized linear model Molar Adolescent Danish population Denmark Sample (statistics) 01 natural sciences Pathology and Forensic Medicine Young Adult 03 medical and health sciences 0302 clinical medicine Radiography Panoramic Statistics Range (statistics) Humans 030216 legal & forensic medicine Age estimation by teeth Mathematics Models Statistical 010401 analytical chemistry Generalized additive model One stage Statistical model 0104 chemical sciences Third molar development Female Molar Third Forensic science Age Determination by Teeth Law Forensic odontology Transition analysis |
| Zdroj: | Arge, S, Wenzel, A, Holmstrup, P, Jensen, N D, Lynnerup, N & Boldsen, J L 2020, ' Transition analysis applied to third molar development in a Danish population ', Forensic Science International, vol. 308, 110145 . https://doi.org/10.1016/j.forsciint.2020.110145 |
| DOI: | 10.1016/j.forsciint.2020.110145 |
| Popis: | Introduction Age assessment based on dental development is often requested in order to assess whether an individual is older or younger than 18 years of age. There are several statistical approaches to estimate age based upon third molar development. The aim of this study was to apply the principles of transition analysis (TA) to a Danish reference material and to evaluate whether it was indicated to include a model that allows for logistic non-linearity as opposed to applying a model only allowing for logistic linearity. For this we chose to use the generalized additive model (gam) and the generalized linear model (glm), respectively. Material and method A cross-sectional sample comprising 1302 panoramic radiographs of Danish subjects in the chronological age range of 13–25 years was included. All present third molars had been scored according to the 10-stage method of Gleiser and Hunt. Each transition from one stage to the subsequent stage was analyzed according to the statistical approach of TA and fitted with both the generalized linear model (glm) and the generalized additive model (gam). In order to assess whether gam or glm was more parsimonious for each transition individually, the Akaikon information criterion (AIC) was applied. Results The results emphasized the importance of applying a statistical model that sufficiently captures the spread of the age estimate. The AIC values showed that some transitions were sufficiently described by glm whereas for others the gam curves fitted significantly better. Conclusion We recommend that for an age assessment tool based on TA, both a fitting allowing for non-linearity and one allowing only for linearity should be included. |
| Databáze: | OpenAIRE |
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