In this chapter, we provide a brief outline of the main motivations why partial order theory is of key importance in the statistical analysis of socio-economic data, presenting some of the more recent tools available for practical applications. We focus in particular on four typical problems in the analysis of socio-economic data, namely: (i) the construction of rankings, (ii) the evaluation of multidimensional latent traits, like deprivation, (iii) the comparison of statistical populations scored on multi-indicator systems and (iv) the measurement of multidimensional ordinal inequality. The exposition has a didactic aim; statistical procedures are sketched avoiding technical details, but discussing simple examples and providing the relevant software code, in the R language.

Fattore, M., Arcagni, A. (2021). Posetic Tools in The Social Sciences: A Tutorial Exposition. In R. Bruggemann, L. Carlsen, T. Beycan, C. Suter, Maggino F (a cura di), Measuring and Understanding Complex Phenomena Indicators and their Analysis in Different Scientific Fields (pp. 219-241). Springer International Publishing [10.1007/978-3-030-59683-5_15].

Posetic Tools in The Social Sciences: A Tutorial Exposition

Fattore, M
;
2021

Abstract

In this chapter, we provide a brief outline of the main motivations why partial order theory is of key importance in the statistical analysis of socio-economic data, presenting some of the more recent tools available for practical applications. We focus in particular on four typical problems in the analysis of socio-economic data, namely: (i) the construction of rankings, (ii) the evaluation of multidimensional latent traits, like deprivation, (iii) the comparison of statistical populations scored on multi-indicator systems and (iv) the measurement of multidimensional ordinal inequality. The exposition has a didactic aim; statistical procedures are sketched avoiding technical details, but discussing simple examples and providing the relevant software code, in the R language.
Capitolo o saggio
Evaluation; Multidimensional ordinal data; Partially ordered set; Ranking;
English
Measuring and Understanding Complex Phenomena Indicators and their Analysis in Different Scientific Fields
Bruggemann, R; Carlsen, L; Beycan, T; Suter, C; Maggino F
2021
978-3-030-59682-8
Springer International Publishing
219
241
Fattore, M., Arcagni, A. (2021). Posetic Tools in The Social Sciences: A Tutorial Exposition. In R. Bruggemann, L. Carlsen, T. Beycan, C. Suter, Maggino F (a cura di), Measuring and Understanding Complex Phenomena Indicators and their Analysis in Different Scientific Fields (pp. 219-241). Springer International Publishing [10.1007/978-3-030-59683-5_15].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/315111
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