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

The quality of life is complex, with human existence closely linked theme. 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 not only multidimensionally but also comprehensively, it is necessary to address the issue of data aggregation. 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 ac-count the potential spatial relationships. However, geographically weighted PCA can capture these relationships. Simple PCA, robust PCA, simple geographically weighted PCA, and robust geographically weighted PCA were tested on the quality of life data. The results of the paper describe differences in selected methods and the possibilities of their applica-tion in the regional evaluation of the quality of life in Europe. Using the PCA, a synthetic quality of life index was constructed based on the defined quality of life indicators on the pan-European scale at the regional level defined by NUTS 2 classification. The result does not bring innovation in terms of the used methods, but it is a challenge in the interpretative level. Comprehensively analyses the topic in a broad spatial scope and detail, compared to the existing studies.