Description
Chair Ioannis Ntzoufras
In recent times, the integration of historical data in the design and analysis of new clinical trials has gained considerable attention, owing to ethical reasons and difficulties encountered in recruiting patients. In the Bayesian framework, the process of informative prior elicitation is widely recognized as a complex and multifaceted undertaking, requiring the careful quantification and...
We propose a novel estimation method for multivariate regime switching models based on a Student-t copula function. These models account for the interdependencies between multiple variables by considering the correlation strength controlled by specific parameters. Moreover, they address fat-tailed distributions through the number of degrees of freedom. These parameters, in turn, are governed...
For the analysis of ordered categorical data, CUB modelling approach entails the estimation of two main structural latent components of the rating process: feeling and uncertainty, parameterized within a two-component mixture of Binomial and uniform distributions: see Piccolo and Simone 2019 for an overview. Featuring parameters can be possibly linked to subject covariates to determine twofold...
Latent class models rely on the conditional
independence assumption, i.e., it is assumed that the categorical
variables are independent given the cluster memberships.
Within the Bayesian framework, we propose a suitable specification of
priors for the latent class model to identify the clusters in
multivariate categorical data where the independence assumption is not
fulfilled. Each...
