Events and Meetings of Italian Statistical Society, Advances in Latent Variables - Methods, Models and Applications

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Measuring multidimensional polarization with ordinal data
Marco Fattore, Alberto Arcagni

Last modified: 2013-06-16

Abstract


In this contribution, we address the problem of measuring well-being polarization with ordinal variables. We introduce a new approach to the problem, discussing an example pertaining to subjective well-being in Italy. The most relevant feature of the proposed methodology is that it is based on partial order theory, a branch of discrete mathematics that allows ordinal data to be formally and consistently handled.

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