1 Citation (Scopus)

Abstract

In this study, a statistical analysis is performed by model the variations of the disabled about 0-19 years old population among French departments. The aim is to classify the departments according to their profile determinants (socioeconomic and behavioural profiles). The analysis is focused on two types of methods: principal component analysis (PCA) and multiple correspondences factorial analysis (MCA) to review which one is the best methods for interpretation of the correlation between the determinants of disability (independent variable). The PCA is the best method for interpretation of the correlation between the determinants of disability (independent variable). The PCA reduces 14 determinants of disability to 4 axes, keeps 80% of total information, and classifies them into 7 classes. The MCA reduces the determinants to 3 axes, retains only 30% of information, and classifies them into 4 classes.

Original languageEnglish
Article number012025
JournalJournal of Physics: Conference Series
Volume855
Issue number1
DOIs
Publication statusPublished - 12 Jun 2017
Event1st International Conference on Mathematics: Education, Theory, and Application, ICMETA 2016 - Surakarta, Indonesia
Duration: 6 Dec 20167 Dec 2016

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