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The quality of life is a complex theme closely linked with human existence. Both scientific and international political organizations have been focusing on this topic in recent decades. This research follows the European Union's challenges to deal with the quality of life as a multi-aspect phenomenon. Firstly, the authors' concept of quality of life, based on key aspects and their respective indicators is introduced. To assess the quality of life multidimensionaly and comprehensively, the issue of data aggregation is addressed. Principal Component Analysis (PCA) is a statistical method used to reduce the dimensionality of the data and can also be used to construct a synthetic index. In its basic form, this method is designed for non-spatial data and does not take into account potential spatial relationships. However, geographically weighted PCA can capture them. Simple PCA, robust PCA, simple geographically weighted PCA, and robust geographically weighted PCA are tested on the quality of life data. The results of the paper describe differences in selected methods and the possibilities of their application in the regional evaluation of the quality of life in Europe. Using the PCA, a synthetic quality of life index is constructed based on the defined quality of life indicators on the pan-European scale at the regional level defined by NUTS 2 classification. Paper, compared to the existing studies, analyses the topic in a broader spatial scope and detail. The results do not bring innovation in terms of the used methods, but mean a challenge in the interpretative level.

Statistická syntéza indikátorů kvality života – návrh tvorby indexu v evropských regionech