Uncertain judgements: eliciting experts' probabilities A O'Hagan, CE Buck, A Daneshkhah, JR Eiser, PH Garthwaite, ... John Wiley & Sons, 2006 | 2121 | 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 | 1361 | 2004 |

Bayesian inference for the uncertainty distribution of computer model outputs J Oakley, A O'hagan Biometrika 89 (4), 769-784, 2002 | 458 | 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 | 352 | 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 | 338 | 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 | 284 | 2014 |

Gaussian process emulation of dynamic computer codes S Conti, JP Gosling, JE Oakley, A O'Hagan Biometrika 96 (3), 663-676, 2009 | 241 | 2009 |

A web-based tool for eliciting probability distributions from experts DE Morris, JE Oakley, JA Crowe Environmental Modelling & Software 52, 1-4, 2014 | 225 | 2014 |

Multivariate Gaussian process emulators with nonseparable covariance structures TE Fricker, JE Oakley, NM Urban Technometrics 55 (1), 47-56, 2013 | 202 | 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 | 180 | 2015 |

Uncertainty analysis and other inference tools for complex computer codes A O'Hagan, MC Kennedy, JE Oakley | 167 | 1998 |

SHELF: the Sheffield elicitation framework (version 2.0) JE Oakley, A O’Hagan School of Mathematics and Statistics, University of Sheffield, UK (http …, 2010 | 142 | 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 | 134 | 2015 |

Estimating percentiles of uncertain computer code outputs J Oakley Journal of the Royal Statistical Society Series C: Applied Statistics 53 (1 …, 2004 | 116 | 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 (1 …, 2012 | 111 | 2012 |

Uncertainty in prior elicitations: a nonparametric approach JE Oakley, A O'Hagan Biometrika 94 (2), 427-441, 2007 | 105 | 2007 |

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 | 99 | 2004 |

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 | 92 | 2004 |

Approximate Bayesian computation and simulation-based inference for complex stochastic epidemic models TJ McKinley, I Vernon, I Andrianakis, N McCreesh, JE Oakley, ... | 83 | 2018 |

Eliciting Gaussian process priors for complex computer codes J Oakley Journal of the Royal Statistical Society Series D: The Statistician 51 (1 …, 2002 | 82 | 2002 |