A semi-bayesian approach for the analysis of scale effects in ordinal regression models

In this paper we propose a semi-Bayesian approach for the analysis of categorical data with an ordered outcome when a scaling component is considered. A recursive partitioning method yielding two trees –one for the location and one for the scaling– is used for selecting covariates, then a Bayesian approach for model estima- tion is implemented and an MCMC sampler is used to obtain posterior estimates. An analysis on risk perception concerning Covid-19 pandemic is carried out to assess the performance of the method