Many social phenomena are complex and difficult to measure and to evaluate. Complexity implies multidimensionality and high level of abstraction. The purpose of this study is to present and compare three main approaches to higher order construct PLS-Path Modelling presented in literature: Repeated indicators, Two-step and Hybrid Approach. Empirical case on Italian Social Cohesion and its result are provided in order to show the methodology and check the reliability of the approaches at issue, choosing the most appropriate among them for social composite indicators.
Higher order construct PLS-PM for Social Composite Indicators / Cataldo, Rosanna; Grassia, MARIA GABRIELLA; Lauro, Natale Carlo; Marino, Marina. - (2015). (Intervento presentato al convegno SIS 2015 Statistical Conference - Statistics and Demography: the Legacy of Corrado Gini tenutosi a Treviso nel 9-11 settembre 2015).
Higher order construct PLS-PM for Social Composite Indicators
CATALDO, ROSANNA;GRASSIA, MARIA GABRIELLA;MARINO, MARINA
2015
Abstract
Many social phenomena are complex and difficult to measure and to evaluate. Complexity implies multidimensionality and high level of abstraction. The purpose of this study is to present and compare three main approaches to higher order construct PLS-Path Modelling presented in literature: Repeated indicators, Two-step and Hybrid Approach. Empirical case on Italian Social Cohesion and its result are provided in order to show the methodology and check the reliability of the approaches at issue, choosing the most appropriate among them for social composite indicators.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
