In social sciences the need often arises to compare and rank groups of respondents by analyzing huge amounts of data and composite indicators are amongst the most effective tools. The paper aims to design an original procedure suitable for ordinal data and able to synthesize subjective evaluations while accounting for both agreement and heterogeneity in response patterns. A composite indicator for ordinal data based on cub models is introduced: the proposal discloses and preserves the heterogeneity also at an aggregated level. Empirical evidence relies on perceived discrimination analysis stemming from the Special Eurobarometer Survey 2015.
A Proposal for a Model-Based Composite Indicator: Experience on Perceived Discrimination in Europe / Capecchi, Stefania; Simone, Rosaria. - In: SOCIAL INDICATORS RESEARCH. - ISSN 0303-8300. - 141:1(2019), pp. 95-110. [10.1007/s11205-018-1848-9]
A Proposal for a Model-Based Composite Indicator: Experience on Perceived Discrimination in Europe
Capecchi Stefania
;Simone Rosaria
2019
Abstract
In social sciences the need often arises to compare and rank groups of respondents by analyzing huge amounts of data and composite indicators are amongst the most effective tools. The paper aims to design an original procedure suitable for ordinal data and able to synthesize subjective evaluations while accounting for both agreement and heterogeneity in response patterns. A composite indicator for ordinal data based on cub models is introduced: the proposal discloses and preserves the heterogeneity also at an aggregated level. Empirical evidence relies on perceived discrimination analysis stemming from the Special Eurobarometer Survey 2015.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
