Formed in 2009, the Archive Team (not to be confused with the archive.org Archive-It Team) is a rogue archivist collective dedicated to saving copies of rapidly dying or deleted websites for the sake of history and digital heritage. The group is 100% composed of volunteers and interested parties, and has expanded into a large amount of related projects for saving online and digital history.
About me
My main research areas include Bayesian methodology, Bayesian parametric and nonparametric modelling, health economic evaluations, decision models, methods for handling missing data, meta-analysis and survival analysis.
Webpages:
- My personal webpage
- My personal blog
- UCL Stats department website
- UCL Primary Care and Population Health department website
- Health Economics Analysis and Research Methods Team (HEART) blog
CV:
See here
Work and Projects
People
- Collaborations
- Michael J. Daniels. Department of Statistics (University of Florida)
- Gianluca Baio. Department of Statistical Science (UCL)
- Rachael Hunter. Department of Primary Care and Population Health (UCL)
- Alexina J. Mason. Department of Health Services Research and Policy (LSHTM)
- Andrea Manca. Centre for Health Economics (University of York)
Papers
Some of the papers published through projects
- Gabrio, A. Daniels, MJ. and Baio, G. 2019. A Bayesian parametric approach to handle missing longitudinal outcome data in trial‐based health economic evaluations. Journal of the Royal Statistical Society: Series A.
- Gabrio, A. Baio, G. and Manca, A. 2019. Bayesian Statistical Economic Evaluation Methods for Health Technology Assessment. Oxford Research Encyclopedia of Economics and Finance.
- Gabrio, A. Mason, JM. and Baio, G. 2019. A full Bayesian model to handle structural ones and missingness in economic evaluations from individual‐level data. Statistics in Medicine 38(8): 1399-1420
- Gabrio, A., Mason, JM. and Baio, G. 2017. Handling Missing Data in Within-Trial Cost-Effectiveness Analysis: a Review with Future Recommendations. PharmacoEconomics-Open 1(2): 79-97
Code
- JAGS code for bivariate Beta-Gamma missing data model with an hurdle approach to handle structural ones in the effectiveness
- JAGS code for longitudinal bivariate Beta-LogNormal pattern mixture model with an hurdle approach to handle structural ones and zeros in the effectiveness and costs
- Some tutorials on writing and fitting Bayesian models using R and JAGS, OpenBUGS or STAN
- MissingHE R package to fit different types of Bayesian models for handling missing data in health economic evaluations