A comparative analysis of rankings of Polish provinces in terms of social cohesion for metric and interval-valued data
Marek Walesiak , Grażyna Dehnel
AbstractThe article describes a comparative analysis of rankings of Polish provinces in terms of social cohesion based on metric and interval-valued data between 1st and 3rd quartiles (50% of observations), 1st and 9th deciles (80% of observations) and the minimum and maximum (100% observations). The rankings were obtained using a hybrid approach combining the use of multidimensional scaling (MDS) with linear ordering. Interval-valued variables characterise the objects of interests more accurately than metric data. Metric data are of an atomic nature, i.e. an observation of each variable is expressed as a single real number. In contrast, an observation of each intervalvalued variable is expressed as an interval. Interval-valued data were derived by aggregating metric data on social cohesion at the level of districts to the province level. All observations were included in the aggregation and then outliers were omitted.
|Publication size in sheets||0.5|
|Book||Papież Monika, Śmiech Sławomir (eds.): The 13th Professor Aleksander Zelias International Conference on Modelling and Forecasting of Socio-Economic Phenomena. Conference Proceedings, Socio-Economic Modelling and Forecasting, 2019, Wydawnictwo C.H. Beck, ISBN 978-83-8158-734-1, 258 p.|
|Keywords in Polish||spójność społeczna, dane symboliczne interwałowe, skalowanie wielowymiarowe, miary agregatowe, obserwacje odstające|
|Keywords in English||social cohesion, interval-valued data, multidimensional scaling, composite indicators, outliers|
|Score||= 20.0, 10-01-2020, ChapterFromConference|
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