The role of simple component analysis in the context of the exploratory methods. An healthcare services evaluation


Among the exploratory techniques, Principal Component Analysis has the best properties in the study of relations between original variables, but in customer satisfaction applications it provides all positive correlations (the first component is an average or a sum of the scores).This feature entails trivial results of little interest that cannot help in decision-making, or even less, rotations (varimax, etc.) that can improve the interpretation of data structure. The aim of this paper is to highlight, via a comparison of methods, the role of Simple Component Analysis to improve the interpretability, over and above the lack of some desirable property (variance explained, etc.).This comparison will be supported by an application to real data on Patient satisfaction in a hospital in Naples.

DOI Code: 10.1285/i2037-3627v1n1p2

Keywords: Principal Component Analysis;Simple Component Analysis;Rotation criteria;Patient Satisfaction

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