Open Conference Systems, 50th Scientific meeting of the Italian Statistical Society

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A new paradigm for rating data models
Domenico Piccolo

Last modified: 2018-06-04


Rating data arise in several disciplines and the class of Generalized Linear Models (GLM) provides a consolidated methodology for their analysis: such structures (and a plethora of variants) model the cumulative probabilities of ordinal scores as functions of subjects’ covariates. A different perspective can be adopted when considering that discrete choices as ordinal assessments are the result of a complex interaction between subjective perception and external circumstances. Thus, an explicit specification of the inherent uncertainty of the data generating process is needed. This paradigm has triggered a variety of researchers and applications, conveying in the unifying framework of GEneralized Mixtures with uncertainty (GEM ) which encompasses also classical cumulative models. Some critical discussions conclude the paper.

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