I am a postdoc researcher in health economics based at Nuffield Department of Primary Care Health Sciences, University of Oxford. My current work focusses on trial-based economic evaluations and observational data analysis for orthopaedic interventions and sleep disorders.
Previously, I did my PhD at the Department of Statistical Science, University College London, under the supervision of Prof Gianluca Baio and Dr Andrea Gabrio.
Broadly, my research interest includes:
- Health economic evaluations
- Missing data
- Bayesian methods in health economics
- Causal inference
Working with Me
Paid health economics internships for undergrads at the University of Oxford
Three paid, eight-week research internships are available for UK undergraduate students at the Nuffield Department of Primary Care Health Sciences, funded by the NIHR.
Interns will work on health economics projects related to dementia and Alzheimer’s disease, supported by a tailored training and seminar programme. The placements run from 3 August to 25 September 2026.
The programme is open to students from any discipline who are not in their final year of study. No prior economics background is required, and we particularly encourage applications from underrepresented groups.
Closing date: 31 May 2026
[Apply here] (www.phc.ox.ac.uk/HEinternship2026)
Selected Publications
Ling, X., Gabrio, A., & Baio, G. (2025). Bayesian Cost-Effectiveness Analysis Using Individual-Level Data is Sensitive to the Choice of Uniform Priors on the Standard Deviations for Costs in Log-Normal Models. PhamarcoEconomics, 43, 1309–1321.
We found that Bayesian cost-effectiveness analyses are sensitive to the choice of the Uniform prior distributions on log cost standard deviations when costs data are assumed to be log-normally distributed and contain zero values.
Ling, X., Gabrio, A., Mason, A., & Baio, G. (2022). A Scoping Review of Item-Level Missing Data in Within-Trial Cost-Effectiveness Analysis. Value in Health, 25(9), 1654-1662.
We identified 87 trial-based CEAs, and found that complete case analysis or available case analysis (CCA/ACA) and multiple imputation (MI) were the most popular methods to handle missing costs and QoL in base-case analysis. However, CCA/ACA dominated sensitivity analysis. Missing costs were widely imputed at item level via MI, while missing QoL was usually imputed at the more aggregated time point level during the follow-up via MI.