Modelling scale effects in rating data: a Bayesian approach

Quality & Quantity, vol. 58, pp. 4053–4071

Abstract

Abstract We present a Bayesian approach for the analysis of rating data when a scaling component is taken into account, thus incorporating a specific form of heteroskedasticity. Model-based probability effect measures for comparing distributions of several groups, adjusted for explanatory variables affecting both location and scale components, are proposed. Markov Chain Monte Carlo techniques are implemented to obtain parameter estimates of the fitted model and the associated effect measures. An analysis on students’ evaluation of a university curriculum counselling service is carried out to assess the performance of the method and demonstrate its valuable support for the decision-making process.

Authors 3

1. Maria Iannario corresponding

   University of Naples Federico II

   Affiliation as printed

   Department of Political Sciences, University of Naples Federico II, Via L. Rodinó, 22, Naples, Italy

2. Maria Kateri Aachen Institute of Statistics

   RWTH Aachen University

   Affiliation as printed

   Institute of Statistics, RWTH Aachen University, Aachen, Germany

3. Claudia Tarantola

   University of Pavia

   Affiliation as printed

   Department of Economics and Management, University of Pavia, Pavia, Italy