A statistical framework for modelling subjective perceptions expressed through ratings is presented. The paper deals with the relationships between personal covariates and self-declared happiness, taking into account several social activities, such as spending time with family and friends, participating in groups and associations, and so on. Our setting concerns a class of statistical models able to measure the effects on life satisfaction of the relational goods which have been proved significant in a large sample of respondents. By means of these models, the proposal enhances the different contributions of subjects’ covariates on their response patterns. The selected approach is based on a mixture model to interpret the assessed perception of two unobserved components, denoted as feeling and uncertainty, respectively, as a blend of real beliefs and indecision. Empirical evidence to support the usefulness of this methodological perspective is provided by a recent observational survey concerning happiness and relational goods.
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Authors gratefully acknowledge Editor and Reviewers for their comments that have improved the current version of the paper. This work has been supported by the SHAPE project within the frame of Programme STAR (CUP: E68C13000020003) at University of Naples Federico II, financially supported by UniNA and Compagnia di San Paolo.
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Capecchi, S., Iannario, M. & Simone, R. Well-Being and Relational Goods: A Model-Based Approach to Detect Significant Relationships. Soc Indic Res 135, 729–750 (2018). https://doi.org/10.1007/s11205-016-1519-7
- Relational goods
- Ordinal data
- cub models