Two methods for composite indicator dimension reduction based on rank correlation

Name: Two methods for composite indicator dimension reduction based on rank correlation
Brand: Vita e Pensiero
Availability: OnlineOnly

digital

Article

Magazine

STATISTICA & APPLICAZIONI

Section

Open Access

Title

Two methods for composite indicator dimension reduction based on rank correlation

Authors

Paolo Cozzucoli, Marco Marozzi

Publisher

Vita e Pensiero

Format

Article |

Pdf

Pages

Online from

02-2015

Issn

1824-6672 (print) | 2283-6659 (digital)

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Description Readers' comments

Composite indicators are very useful in addressing complex variables that cannot be directly observed: they can be used to assess for example quality of life and customer satisfaction. In practice, it is very often of interest to reduce the dimension of a composite indicator by selecting among its components the most important ones. In this paper we propose a method for reducing the dimension of composite indicators based on the comparison of rank correlation coefficients and we compare it with another method. A practical application to university student satisfaction data is presented. Moreover, we evaluate how the choice of the rank correlation coefficient influences the results of the practical application.

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