TY - JOUR
T1 - Population Analysis of Disabled Children by Departments in France
AU - Meidatuzzahra, Diah
AU - Kuswanto, Heri
AU - Pech, Nicolas
AU - Etchegaray, Amélie
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2017/6/12
Y1 - 2017/6/12
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85023608228&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/855/1/012025
DO - 10.1088/1742-6596/855/1/012025
M3 - Conference article
AN - SCOPUS:85023608228
SN - 1742-6588
VL - 855
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012025
T2 - 1st International Conference on Mathematics: Education, Theory, and Application, ICMETA 2016
Y2 - 6 December 2016 through 7 December 2016
ER -