Measuring the Quality of Life Using Multiple Factor Analysis for Contingency Tables
Journal Title: Scholars Journal of Physics, Mathematics and Statistics - Year 2016, Vol 3, Issue 4
Abstract
The aim of this study is to measure European countries of the quality of life scores compared to a demographic variables of gender using multiple factor analysis for contingency tables (MFACT). The goal of multiple factor analysis (MFA) is to integrate different groups of variables describing the same observations. MFA is used in very different domains. For example, when a quality of life survey is performed in different countries, specific problems arise, ranging from obtaining equivalent questionnaires to managing the comparison of social features. In this study we showed the use of MFACT applied to a quality of life survey conducted by Eurofound (2003). We took European countries of the quality of life survey in analysis. We analyzed four variable categories (Afford, Attitude, Satisfaction and Quality) according to countries and gender by MFA. The results of the MFA started with the analysis of the eigenvalues of the weighted principal component analysis (PCA). We had almost 71% of the variability in the first two factors. We found that it wasn’t important gender for quality of life. It was obtained EU member countries were very close, acceding countries were very close and candidate countries are very close according to country groups. We examined quality of life survey’s variables in four categories according to gender in this study. It can be examined variables according to the other demographic variables like education level, age and etc.
Authors and Affiliations
Zerrin Aşan Greenacre, Alper Bekki
Keywords
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