My main interests are in Bayesian statistical modelling for cost-effectiveness analysis and decision-making problems in the health systems. During my PhD I have specifically focused on the study and adoption of Bayesian methods to handle missing data in health economic evaluations and to assess the impact of their uncertainty on the output of the decision-making process. My research area involves different topics: from systematic literature reviews, case study applications, survival analysis, meta-analytic methods, multilevel models and trial-based clinical and economic analyses. Here you can find my CV with more details on what I have done so far and my interests.
I am very interested in the analysis of longitudinal data, with a focus on different types of statistical methods to deal with missingness. My preferred statistical programming software and the one I am most familiar with is R/RStudio by far, but I do also possess a good knowledge of other software such as STATA and MATLAB. I am quite expert in the use of free open-source Bayesian software programs, such as OpenBUGS, JAGS and STAN.
I graduated in Applied Economics from the University of Pavia (Italy) and in Statistics and Econometrics from the University of Essex (UK), and I have completed a PhD in Statistics in the Department of Statistical Science at University College London