A. Gabrio

Research profile

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. Within the health economic framework, my research interest extends to the analysis of longitudinal data using different types of statistical methods to deal with missingness in a principled way. 

Research projects
  • Nonignorable Missingness Models in HTA
  • Short course on missing data in HTA (GitHub rep)
  • Bayesian Methods for Health Technology Assessment
  • Bayesian Modelling for Health Economic Evaluations
  • Missingness Methods in trial-based CEA
  • R package: MissingHE (CRAN rep)
  • Bayesian Hierarchical Models for the Prediction of Volleyball Results

See an overview of my current and past research projects here

Key publications
Gabrio, A., Daniels, M., & Baio, G. (2020). A Bayesian parametric approach to handle missing longitudinal outcome data in trial based health economic evaluations. Journal of the Royal Statistical Society Series A-Statistics in Society, 183(2), 607-629. https://doi.org/10.1111/rssa.12522
More information about this publication
Recent publications
Other publications

https://scholar.google.co.uk/citations?user=2fPE3iAAAAAJ&hl

Notes

Check out my GitHub page and my personal website for more info on what I do and how to get in contact with me about some research projects