[Forum SIS] Spostamento data seminario Paola Zuccolotto presso Dipartimento di Scienze Economiche, Università di Verona

[Luigi Grossi]

AVVISO DI SPOSTAMENTO DATA SEMINARIO

Si annuncia lo spostamento del seminario della prof.ssa Paola Zuccolotto
precedentemente fissato in data 25 febbraio 2015.

 

Università di Verona - Dipartimento di Scienze Economiche

Via dell'artigliere, 19

Verona

 

Mercoledì 11 marzo 2015 alle ore 12.30 - Aula C, Palazzo di Economia

 "Modeling rating data with Nonlinear CUB models"

Relatore: Paola Zuccolotto - Università di Brescia

 


Riassunto


The analysis of human perceptions is often carried out by resorting to
questionnaires, where respondents are asked to express ratings about the
objects being evaluated. The goal of the statistical tools proposed for this
kind of data is to explicitly characterize the respondents' perceptions
about a latent trait, by taking into account, at the same time, the ordinal
categorical scale of measurement of the involved statistical variables. The
seminar deals with a statistical model for rating data, obtained starting
from a particular assumption about the unconscious mechanism driving
individuals' responses on a rating scale. The basic idea derives from the
founding paradigm of CUB models (Piccolo, 2003; D'Elia and Piccolo, 2005;
Iannario and Piccolo, 2012). The described model is called Nonlinear CUB
(Manisera and Zuccolotto, 2014). The main innovation of Nonlinear CUB models
is that, in their framework, it is possible to define the new concept of
transition probability, i.e. the probability of increasing one rating point
at a given step of the decision process. Transition probabilities and the
related transition plots are able to describe the state of mind of the
respondents about the response scale used to express judgments. In
particular, NLCUB can address the (possible) unequal spacing of the rating
categories, that occurs when respondents, in their unconscious search for
the ``right'' response category, find it easier to move, for example, from
rating 1 to 2 than from rating 4 to 5. This corresponds to the concept of
``nonlinearity'' introduced by NLCUB models, defined as the nonconstantness
of the transition probabilities. Case studies on real data are presented, in
order to show the functioning of the model. R functions are available for
computations. Research partially funded by STAR project (University of
Naples Federico II) and partially by a grant from the European Union Seventh
Framework Programme (SYstemic Risk TOmography: Signals, Measurements,
Transmission Channels, and Policy Interventions - SYRTO).

 

 

Cordiali saluti,

Luigi Grossi

 

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