I am a Reader in the School of Mathematics and Statistics at the University of Sheffield. My research interests are in Bayesian statistics, in particular analysing uncertainty in complex computer models, eliciting probability distributions, and applications in Health Economics.
School of Mathematics and Statistics
The Hicks Building
+44 114 2223853
j.oakley at sheffield.ac.uk
- A new journal on uncertainty in computer models has been launched by the Society for Industrial and Applied Mathematics, and the American Statistical Association: the SIAM/ASA Journal on Uncertainty Quantification (JUQ).
- I have helped write draft guidance on expert elicitation in risk assessment for the European Food Safety Authority. The draft guidance is open to public consultation, and is available from here.
- Morris, D. E., Oakley, J. E. and Crowe, J. A. (2014). A web-based tool for eliciting probability distributions from experts. Environmental Modelling & Software, 52, 1-4.
- Strong, M. and Oakley, J. E. When is a model good enough? Deriving the expected value of model improvement via specifying internal model discrepancies. To appear in SIAM/ASA Journal on Uncertainty Quantification.
- Strong, M, Oakley, J. E. and Brennan A. Estimating multi-parameter partial Expected Value of Perfect Information from a probabilistic sensitivity analysis sample: a non-parametric regression approach. To appear in Medical Decision Making.
- Ren, S. and Oakley, J. E. (2013). Assurance calculations for planning clinical trials with time-to-event outcomes. To appear in Statistics in Medicine. Download supporting R code.
- Strong, M. and Oakley, J. E. (2013). An efficient method for computing single parameter partial expected value of perfect information. Medical Decision Making, 33, 755-766.