Modelling Subjective Well-Being dimensions through an IRT bifactor model: Evidences from an Italian study
The investigation of individual and community well-being has acquired a particular relevance over time for governments to develop strategies and identify resources for improving standards of living. To this aim, it is necessary to analyse changes at the overall level and examine how subjective well-being differs between different sub-groups of the population as well as across local areas. Using data measuring the well-being of residents in the Romagna area (Italy), we propose a multidimensional approach within the item response theory (IRT) framework to estimate an overall score of community Subjective Well-Being (SWB) and individual scores reflecting specific dimensions, taking into account for the ordinal polytomous nature of the items. The results show that aspects dealing with Life Evaluation mainly affect the overall SWB, while issues pertaining to Community and Environment are less important. The proposed approach is effective in developing an indicator taking into account the multidimensionality of SWB and estimating individual scores reflecting the heterogeneity among residents.
Subjective Well-Being; graded response data; item response theory; bifactor model