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Open AccessArticle

Classification Maps in Studies on the Retirement Threshold

1
Department of Quality of Life Research, Medical University of Gdańsk, 80-210 Gdańsk, Poland
2
Department of Radiological Informatics and Statistics, Medical University of Gdańsk, 80-210 Gdańsk, Poland
3
Department of Nuclear Medicine, Medical University of Gdańsk, 80-210 Gdańsk, Poland
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(4), 1282; https://doi.org/10.3390/app10041282 (registering DOI)
Received: 20 January 2020 / Revised: 6 February 2020 / Accepted: 8 February 2020 / Published: 14 February 2020
(This article belongs to the Special Issue Medical Informatics and Data Analysis)
The aim of this work is to present new classification maps in health informatics and to show that they are useful in data analysis. A statistical method, correspondence analysis, has been applied for obtaining these maps. This approach has been applied to studies on expectations and worries related to the retirement threshold. For this purpose two questionnaires formulated by ourselves have been constructed. Groups of individuals and their answers to particular questions are represented by points in the classification maps. The distribution of these points reflects psychological attitudes of the considered population. In particular, we compared structures of the maps searching for factors such as gender, marital status, kind of work, economic situation, and intellectual activity related to the attendance the University of the Third Age, which are essential at the retirement threshold. Generally, in Polish society, retirement is evaluated as a positive experience and the majority of retirees do not want to return to their professional work. This result is independent of the kind of work and of the gender. View Full-Text
Keywords: medical informatics; statistical computing; data analysis; retirement threshold medical informatics; statistical computing; data analysis; retirement threshold
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Bielińska, A.; Bielińska-Wa̧ż, D.; Wa̧ż, P. Classification Maps in Studies on the Retirement Threshold. Appl. Sci. 2020, 10, 1282.

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