Jeremy Oakley
Jeremy Oakley
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Cited by
Uncertain judgements: eliciting experts' probabilities
A O'Hagan, CE Buck, A Daneshkhah, JR Eiser, PH Garthwaite, ...
John Wiley & Sons, 2006
Probabilistic sensitivity analysis of complex models: a Bayesian approach
JE Oakley, A O'Hagan
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2004
Bayesian inference for the uncertainty distribution of computer model outputs
J Oakley, A O'Hagan
Biometrika 89 (4), 769-784, 2002
A systematic review and economic evaluation of alendronate, etidronate, risedronate, raloxifene and teriparatide for the prevention and treatment of postmenopausal osteoporosis.
M Stevenson, ML Jones, E De Nigris, N Brewer, S Davis, J Oakley
Health technology assessment (Winchester, England) 9 (22), 1-160, 2005
Probability is perfect, but we can't elicit it perfectly
A O'Hagan, JE Oakley
Reliability Engineering & System Safety 85 (1-3), 239-248, 2004
Estimating multiparameter partial expected value of perfect information from a probabilistic sensitivity analysis sample: a nonparametric regression approach
M Strong, JE Oakley, A Brennan
Medical Decision Making 34 (3), 311-326, 2014
Gaussian process emulation of dynamic computer codes
S Conti, JP Gosling, JE Oakley, A O'Hagan
Biometrika 96 (3), 663-676, 2009
A web-based tool for eliciting probability distributions from experts
DE Morris, JE Oakley, JA Crowe
Environmental Modelling & Software 52, 1-4, 2014
Multivariate Gaussian process emulators with nonseparable covariance structures
TE Fricker, JE Oakley, NM Urban
Technometrics 55 (1), 47-56, 2013
Bayesian history matching of complex infectious disease models using emulation: a tutorial and a case study on HIV in Uganda
I Andrianakis, IR Vernon, N McCreesh, TJ McKinley, JE Oakley, ...
PLoS computational biology 11 (1), e1003968, 2015
Estimating percentiles of uncertain computer code outputs
J Oakley
Journal of the Royal Statistical Society: Series C (Applied Statistics) 53 …, 2004
SHELF: the Sheffield elicitation framework (version 2.0)
JE Oakley, A O’Hagan
School of Mathematics and Statistics, University of Sheffield, UK (http …, 2010
Estimating the expected value of sample information using the probabilistic sensitivity analysis sample: a fast, nonparametric regression-based method
M Strong, JE Oakley, A Brennan, P Breeze
Medical Decision Making 35 (5), 570-583, 2015
Methods for expected value of information analysis in complex health economic models: developments on the health economics of interferon-beta and glatiramer acetate for …
P Tappenden, JB Chilcott, S Eggington, J Oakley, C McCabe
Health technology assessment (Winchester, England) 8 (27), iii, 1-78, 2004
Managing structural uncertainty in health economic decision models: a discrepancy approach
M Strong, JE Oakley, J Chilcott
Journal of the Royal Statistical Society: Series C (Applied Statistics) 61 …, 2012
Uncertainty in prior elicitations: a nonparametric approach
JE Oakley, A O'Hagan
Biometrika 94 (2), 427-441, 2007
Gaussian process modeling in conjunction with individual patient simulation modeling: a case study describing the calculation of cost-effectiveness ratios for the treatment of …
MD Stevenson, J Oakley, JB Chilcott
Medical Decision Making 24 (1), 89-100, 2004
Modelling the expected net benefits of interventions to reduce the burden of medication errors
J Karnon, A McIntosh, J Dean, P Bath, A Hutchinson, J Oakley, N Thomas, ...
Journal of health services research & policy 13 (2), 85-91, 2008
Eliciting Gaussian process priors for complex computer codes
J Oakley
Journal of the Royal Statistical Society: Series D (The Statistician) 51 (1 …, 2002
Simulation sample sizes for Monte Carlo partial EVPI calculations
JE Oakley, A Brennan, P Tappenden, J Chilcott
Journal of health economics 29 (3), 468-477, 2010
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