CUB models and related issues: a framework for the analysis of ordinal data
The talk will focus on the statistical interpretation of general framework for modelling ordinal data. The rationale stems from the interpretation of the respondent’s final choice as a weighted combination of a personal feeling and some intrinsic uncertainty. A mixture of these components (explained by discrete random variables) has been defined CUB model. This approach has been applied in different fields as Marketing, Medicine, Sensory analysis, Evaluation and Policy studies, Psychology, Urban emergencies, Linguistic analyses, Risk perception, Subjective probabilities, and so on.
Some empirical evidence referred to real data sets will be presented to support the usefulness of the approach.