Tony O'Hagan - Academic pages

Research papers by Tony O'Hagan.

Here are details of my papers since 1997. There are abstracts available for almost all, and you can download those papers that are as yet unpublished.

Papers preceded by letter codes (CC), (HE) or (EL) are in my three most active areas of research (uncertainty in computer codes, health economics and elicitation). If you click on these, they link to the relevant topic on my research page.

Papers are listed in 2 categories: unpublished and published,

Unpublished papers

• O'Hagan, A., Cox, M. and Wright, L. (2022). Anomalous behaviour of the Welch-Satterthwaite approximation. Submitted to Journal of Applied Statistics. [Abstract] [Download, pdf format]

• (CC) O'Hagan, A. (2013). Polynomial Chaos: A Tutorial and Critique from a Statistician's Perspective. Submitted to SIAM/ASA Journal of Uncertainty Quantification. This paper was intended to spark a debate, and hopefully for an applied mathematician to write in support of polynomial chaos. But this didn't happen and although it was submitted to a journal they kept it forever without making any decision. [Abstract] [Download, pdf format]

• Harris, K., O'Hagan, A. and Quegan, S. (2009). The impact of satellite-derived land-cover uncertainty on carbon cycle calculations. This short paper presents the results of combining the methods of uncertainty quantification in Kennedy et al (2008) and Cripps, O'Hagan and Quaife (2013). [Abstract] [Download] [Supporting technical report]

• (CC) Gosling, J. P. and O'Hagan, A. (2007). Understanding the uncertainty in the biospheric carbon flux for England and Wales. Research Report No. 567/06. Department of Probability and Statistics, The University of Sheffield. This paper is a supporting document for the Kennedy et al (2008) paper. [Abstract] [Download, pdf format]

• O'Hagan, A., Crane, M., Grist, E. P. M. and Whitehouse, P. (2005). Estimating species sensitivity distributions with the aid of expert judgements. Research Report No. 556/05, Department of Probability and Statistics, University of Sheffield. This paper was rejected by Applied Statistics on the grounds that the application had already been published. Nevertheless, it contains technical material that has not been published, and serves as a supporting document for Grist et al (2006). [Abstract] [Download, pdf format]

• Kornak, J., O'Hagan, A. and Haggard, M. (2005). A Bayesian multiplicative Markov random field model for determining activated areas in functional magnetic resonance imaging studies. This paper was submitted to Journal of the American Statistical Association and in February 2006 we were invited to revise and resubmit following comments from reviewers. The lead author has never found the time to revise, and it seems unlikely now that it ever will be resubmitted. Nevertheless, the paper has been downloaded from this page hundreds of times and seems to be of general interest. [Abstract] [Download, pdf format]

• (CC) O'Hagan, A. (1998). A Markov property for covariance structures. Nottingham University Statistics Research Report 98-13. This paper is now a supporting document for the Kennedy and O'Hagan (2001) paper. [Abstract] [Download, pdf format] [Download, postscript]

• Green, P. and O'Hagan, A. (1998). Model choice with MCMC on product spaces without using pseudo-priors. Nottingham University Statistics Research Report 98-01. This paper is referred to by various other authors but has never been submitted for publication. [Abstract] [Download, pdf format] [Download, postscript]

• O'Hagan, A. (1976). Moments of the truncated multivariate-t distribution. This paper was submitted to Journal of the Royal Statistical Society, Series B and immediately rejected by the editor who claimed that the results could be more easily proved by using the fact that the multivariate-t is a scale mixture of the multivariate normal. When I showed him that this was false, he again immediately rejected the paper, this time on the grounds that the results were not sufficiently interesting to justify the number of pages needed to prove them. I believe that there is continuing interest in this topic, so I have had the original technical report scanned. [Abstract] [Download, pdf format]

Published papers

• O'Hagan, A. and Cox, M. (2023). Simple informative prior distributions for metrology. Metrologia 60, 025003. doi: 10.1088/1681-7575/acb93d [Abstract] [Download, pdf format]

• (EL) Holzhauer, B., Hampson, L.V., Gosling, J.P., Bornkamp, B., Kahn, J., Lange, M.R., Luo, W-L., Brindicci, C., Lawrence, D., Ballerstedt, S. and O'Hagan, A. (2022) Eliciting judgements about dependent quantities of interest: The SHeffield ELicitation Framework extension and copula methods illustrated using an asthma case study. Pharmaceutical Statistics 21, 1005-1021. doi: 10.1002/pst.2212 [Abstract]

• Cox, M. and O'Hagan, A. (2022) Meaningful expression of uncertainty in measurement. Accreditation and Quality Assurance, 27, 19-37. doi: 10.1007/s00769-021-01485-5 [Abstract] [Open access download]

• (EL) Jurek, L., Balthazar, M., Gulati, S., Novakovic, N., Núñez, M., Oakley, J. and O'Hagan, A. (2021). Response (minimum clinically relevant change) in ASD symptoms after an intervention according to CARS-2: consensus from an expert elicitation procedure. European Child and Adolescent Psychiatry 31, 1-10. doi: 10.1007/s00787-021-01772-z [Abstract]

• Neuenschwander, B., Weber, S., Schmidli, H. and O'Hagan, A. (2020). Predictively Consistent Prior Effective Sample Sizes. Biometrics 76, 578-587 (with discussion 588-605), doi: 10.1111/biom.13252 [Abstract]

• (EL) O'Hagan, A. (2019). Expert knowledge elicitation: Subjective but scientific. The American Statistician 73:sup1, 69-81, doi: 10.1080/00031305.2018.1518265. [Abstract]

• Brownstein, N. C., Louis, T. A., O'Hagan, A. and Pendergast, J. (2019). The role of expert judgement in statistical inference and evidence-based decision-making. The American Statistician, 73:sup1, 56-68, doi: 10.1080/00031305.2018.1529623. [Abstract]

• Schmidli, H., Gsteiger, S., Roychoudhury, S., O'Hagan, A., Spiegelhalter, D. and Neuenschwander, B. (2014). Robust meta-analytic-predictive priors in clinical trials with historical control information. Biometrics 70, 1023-1032. [Abstract]

• (EL) Zapata-Vazquez, R., O'Hagan, A. and Bastos, L. S. (2014). Eliciting expert judgements about a set of proportions. Journal of Applied Statistics 41, 1919-1933. [Abstract]

• (CC) Brynjarsdottir, J. and O'Hagan, A. (2014). Learning about physical parameters: The importance of model discrepancy. Inverse Problems, 30, 114007 (24pp), November 2014. [Abstract]

• (EL) O'Hagan, A. (2014). Eliciting and using expert knowledge in metrology. Metrologia 15, S237-S244. [Abstract]

• (CC) Cripps, E., O'Hagan, A. and Quaife, T. (2013). Quantifying uncertainty in remotely sensed land cover maps. Stochastic Environmental Research and Risk Assessment 27, 1239-1251. [Abstract]

• (HE) Griffiths, R.I., Gleeson, M.L., Danese, M.D. and O’Hagan, A. (2012). Inverse probability weighted least squares regression in the analysis of time-censored cost data: an evaluation of the approach Using SEER-Medicare. Value in Health 15, 656-663. [Abstract]

• O'Hagan, A. and Pericchi, L. (2012). Bayesian heavy-tailed models and conflict resolution: a review. Brazilian Journal of Probability and Statistics 26, 372-401. [Abstract]

• (HE) Griffiths, R.I., Barron, R.L., Gleeson, M.L., Danese, M.D., O’Hagan, A., Chia, V.M., Legg, J.C. and Lyman, G.H. (2012). Granulocyte-colony stimulating factor use and medical costs after initial adjuvant chemotherapy in older patients with early-stage breast cancer. Pharmacoeconomics 30, 103-118. [Abstract]

• (EL) O'Hagan, A. (2012). Probabilistic uncertainty specification: Overview, elaboration techniques and their application to a mechanistic model of carbon flux. Environmental Modelling and Software 36, 35-48. [Abstract]

• Witte, S., Schmidli, H., O'Hagan, A. and Racine, A. (2011). Designing a non-inferiority study in kidney transplantation: a case study. Pharmaceutical Statistics 10, 427–432. [Abstract]

• Andrade, J. A. A. and O'Hagan, A. (2011). Bayesian robustness modelling of location and scale parameters. Scandinavian Journal of Statistics 38, 691-711. [Abstract]

• (HE) Mihaylova, B., Briggs, A., O'Hagan, A. and Thompson, S. G. (2011). Review of statistical methods for analysing healthcare resources and costs, applicable to clinical trial data. Health Economics 20, 897-916. [Abstract]

• Schmidt, A. M., Guttorp, P. and O'Hagan, A. (2011). Considering covariates in the covariance structure of spatial processes. Environmetrics 22, 487-500. [Abstract]

• (HE) Kharroubi, S. A., Brazier, J. E. and O'Hagan, A. (2010). A comparison of United States and United Kingdom EQ-5D health state valuations using a nonparametric Bayesian method. Statistics in Medicine, 29, 1622-1634. [Abstract]

• (EL) Moala, F.M. and O'Hagan, A. (2010). Elicitation of multivariate prior distributions: a nonparametric Bayesian approach. Journal of Statistical Planning and Inference 140, 1635-1655. [Abstract]

• (CC) Conti, S. and O'Hagan, A. (2010). Bayesian emulation of complex multi-output and dynamic computer models. Journal of Statistical Planning and Inference 140, 640-651. [Abstract]

• Heiner, K. W., Kennedy, M. C. and O'Hagan, A. (2010). Sequential multilocation auditing and the New York food stamps program. In The Oxford Handbook of Applied Bayesian Analysis, O'Hagan, A. and West, M. (eds.), pp 653-678. Oxford University Press, Oxford.

• (HE) Nixon, R.M., O'Hagan, A., Oakley, J.E., Madan, J., Stevens, J.W. Bansback, N. and Brennan, A. (2009) The Rheumatoid Arthritis Drug Development Model: A case study in Bayesian clinical trial simulation. Pharmaceutical Statistics 8, 371-389. [Abstract]

• (CC) Bastos, L. S. and O'Hagan, A. (2008). Diagnostics for Gaussian process emulators. Technometrics 51, 425-438. [Abstract]

• (CC) Conti, S., Gosling, J. P., Oakley, J. E. and O'Hagan, A. (2009). Gaussian process emulation of dynamic computer codes. Biometrika 96, 663-676. [Abstract]

• (HE) Pickin, M., Cooper, C.L., Chater, T., O'Hagan, A., Abrams, K.R., Cooper, N.J., Boggild, M. Palace, J., Ebers, G., Chilcott, J.B., Tappenden, P. and Nicholl, J. (2009). The Multiple Sclerosis Risk Sharing Scheme Monitoring Study – early results and lessons for the future. BMC Neurology. 9:1. [Abstract] [Published online at http://www.biomedcentral.com/1471-2377/9/1/abstract]

• (HE) McCabe, C., Claxton, K. and O'Hagan, A. (2008). Why licensing authorities need to consider the net value of new drugs in assigning review priorities: Addressing the tension between licensing and reimbursement. International Journal of Technology Assessment in Health Care 24, 140-145. [Abstract]

• (CC) Kennedy, M. C., O'Hagan, A., Anderson, C. W., Lomas, M., Woodward, F. I., Heinemeyer, A. and Gosling, J. P. (2008). Quantifying uncertainty in the biospheric carbon flux for England and Wales. Journal of the Royal Statistical Society, Series A 171, 109-135. [Abstract] [See also Gosling and O'Hagan (2007) in my other papers for supporting details]

• (EL) Gosling, J.P., Oakley, J.E. and O'Hagan, A. (2007). Nonparametric elicitation for heavy-tailed prior distributions. Bayesian Analysis 2, 693-718. [Abstract] [Published online].

• (HE) O'Hagan, A., Stevenson, M. and Madan, J. (2007). Monte Carlo probabilistic sensitivity analysis for patient level simulation models: Efficient estimation of mean and variance using ANOVA. Health Economics 16, 1009-1023. [Abstract]

• (HE) Brennan, A., Kharroubi, S. A., O'Hagan, A. and Chilcott, J. (2007) Calculating partial expected value of information in cost-effectiveness models. Medical Decision Making 27, 448-470. [Abstract]

• (EL) Oakley, J. E. and O'Hagan, A. (2007). Uncertainty in prior elicitations: a nonparametric approach. Biometrika 94, 427-441. [Abstract]

• Boxall, J. B., O'Hagan, A., Pooladsaz, S., Saul, A. J. and Unwin, D. M. (2007). Estimation of burst rates in water distribution mains. Water Management 160, 73-82. [Abstract]

• (HE) Kharroubi, S. A., Brazier, J. E., Roberts, J. and O'Hagan, A. (2007). Modelling SF-6D health state preference data using a nonparametric Bayesian method. Journal of Health Economics 26, 597-612. [Abstract]

• (HE) Kharroubi, S. A., Brazier, J. E. and O'Hagan, A. (2007). Modelling covariates for the SF-6D standard gamble health state preference data using a nonparametric Bayesian method. Social Science and Medicine, 64, 1242-1252. [Abstract]

• Tancredi, A., Anderson, C. W. and O'Hagan, A. (2006). Accounting for threshold uncertainty in extreme value estimation. Extremes 9, 87-106. [Abstract]

• (EL) O'Hagan, A. (2006). Research in elicitation. In Bayesian Statistics and its Applications, S. K. Upadhyay, U. Singh and D. K. Dey (eds.), 375-382. Anamaya: New Delhi. [Abstract]

• (CC) O'Hagan, A. (2006). Bayesian analysis of computer code outputs: a tutorial. Reliability Engineering and System Safety, 91, 1290-1300. [Abstract] [Download original technical report, pdf format]

• (CC) Kennedy, M. C., Anderson, C. W., Conti, S. and O'Hagan, A. (2006). Case studies in Gaussian process modelling of computer codes. Reliability Engineering and System Safety, 91, 1301-1309. [Abstract]

• O'Hagan, A. (2006). Science, subjectivity and software (comments on the articles by Berger and Goldstein). Bayesian Analysis 1, 445-450. [Abstract] [Published online]

• (HE) McCabe C., Brazier, J., Gilks, P., Tsuchiya, A., Roberts, J., O'Hagan, A., Stevens, K. (2006). Using rank data to estimate health state utility models. Journal of Health Economics 25, 418-431. [Abstract]

• Grist, E. P. M., O'Hagan, A, Crane, M., Sorokin, N., Sims, I. and Whitehouse, P. (2006). Bayesian and time-independent species sensitivity distributions for risk assessment of chemicals. Environmental Science and Technology 40, 395-401. [Abstract] [See O'Hagan et al (2005) in my other papers for technical details]

• Buck, C. E., Gomez Portugal Aguilar, D., Litton, C. D. and O'Hagan, A. (2006). Bayesian nonparametric estimation of the radiocarbon calibration curve. Bayesian Analysis 1, 265-288. [Published online] [Abstract]

• Andrade, J. A. A. and O'Hagan, A. (2006). Bayesian robustness modelling using regularly varying distributions. Bayesian Analysis 1, 169-188. [Published online] [Abstract]

• (HE) O'Hagan, A., Stevens, J. W. and Campbell, M. J. (2005). Assurance in clinical trial design. Pharmaceutical Statistics 4, 187-201. [Abstract] [WinBUGS files for examples: Example 3, Example 4]

• (HE) O’Hagan, A., McCabe, C., Akeurst, R., Brennan, A., Briggs, A., Claxton, K., Fenwick, E., Fryback, D., Sculpher, M., Spiegelhalter, D. and Willan, A. (2005). Incorporation of uncertainty in health economic modelling studies. PharmacoEconomics 23, 529-536. [Abstract]

• (HE) Claxton, K., Sculpher, M., McCabe, C., Briggs, A., Buxton, M., Brazier, J., Akeurst, R. and O’Hagan, A. (2005). Probabilistic sensitivity analysis for NICE technology assessment: not an optional extra. Health Economics, 14, 339-347. [Abstract]

• (EL) Garthwaite, P. H., Kadane, J. B. and O'Hagan, A. (2005). Statistical methods for eliciting probability distributions. Journal of the American Statistical Association, 100, 680-701. [Abstract]

• (HE) Kharroubi, S. A., O'Hagan, A. and Brazier, J. E. (2005). Estimating utilities from individual health state preference data: a nonparametric Bayesian method. Applied Statistics 54, 879-895. [Abstract]

• Papathomas, M. and O'Hagan, A. (2005). Updating beliefs for binary variables. Journal of Statistical Planning and Inference 135, 324-338. [Abstract]

• (CC) Oakley, J. and O'Hagan, A. (2004). Probabilistic sensitivity analysis of complex models: a Bayesian approach. Journal of the Royal Statistical Society, Series B 66, 751-769. [Abstract]

• (HE) O'Hagan, A. and Stevens, J. W.(2004). On estimators of medical costs with censored data. Journal of Health Economics 23, 615-625. [Abstract]

• (CC, EL) O'Hagan, A. and Oakley, J. E. (2004). Probability is perfect, but we can't elicit it perfectly. Reliability Engineering and System Safety 85, 239-248. [Abstract]

• (HE) Chilcott, J., McCabe, C., Tappenden, P., O'Hagan, A., Cooper, N. J., Abrams, K. and Claxton, K. (2003). Modelling the cost effectiveness of interferon beta and glatiramer acetate in the management of multiple sclerosis. British Medical Journal 326, 522-526. [Abstract]

• (HE) Stevens, J. W., O'Hagan, A. and Miller, P. (2003). Case study in the Bayesian analysis of a cost-effectiveness trial in the evaluation of health care technologies: Depression. Pharmaceutical Statistics, 2, 51-68. [Abstract] [Download WinBUGS files as in Appendix A, Appendix B, and Appendix C]

• Schmidt, A. M. and O'Hagan, A. (2003). Bayesian inference for nonstationary spatial covariance structure via spatial deformations. Journal of the Royal Statistical Society, Series B, 65, 745-758. [Abstract]

• Bozza, S. and O'Hagan, A. (2003). A Bayesian approach for the estimation of the covariance structure of separable spatio-temporal stochastic processes. In Between Data Science and Applied Data Analysis, M. Schader, W. Gaul and M. Vichi (eds), 165-172. Springer-Verlag. [Abstract]

• (HE) van Hout, B. A., Gagnon, D. D., McNulty, P. and O’Hagan, A. (2003). The cost-effectiveness of two new antiepileptic therapies in the absence of direct comparative data: a first approximation. PharmacoEconomics, 21, 315-326. [Abstract]

• O'Hagan, A. (2003). HSSS model criticism (with discussion). In Highly Structured Stochastic Systems, P. J. Green, N. L. Hjort and S. T. Richardson (eds), 423-453 Oxford University Press.

• (HE) O'Hagan, A. and Stevens, J. W. (2003). Assessing and comparing costs: How robust are the bootstrap and methods based on asymptotic normality? Health Economics 12, 33-49. [Abstract]

• (HE) Stevens, J. W. and O'Hagan, A. (2002). Incorporation of genuine prior information in cost-effectiveness analysis. International Journal of Technology Assessment in Health Care, 18, 782-790. [Abstract]

• (HE) O'Hagan, A. and Stevens, J. W. (2002). Bayesian methods for design and analysis of cost-effectiveness trials in the evaluation of health care technologies. Statistical Methods in Medical Research, 11, 469-490. [Abstract]

• (CC) Oakley, J. and O'Hagan, A. (2002). Bayesian inference for the uncertainty distribution of computer model outputs. Biometrika 89, 769-784. [Abstract]

• Laws, D. J. and O'Hagan, A. (2002). A hierarchical Bayes model for rare errors. The Statistician 51, 431-450. [Abstract]

• (HE) O'Hagan, A. and Stevens, J. W.(2002). The probability of cost-effectiveness. BMC Medical Research Methodology 2: 5. [Abstract] [View on BMC website] [Download, pdf format]

• Gomez Portugal Aguilar, D., Litton, C. D. and O'Hagan, A. (2002). Novel statistical model for a piece-wise linear radiocarbon calibration curve. Radiocarbon 44, 195-212. [Abstract]

• (CC) Kennedy, M., O'Hagan, A. and Higgins, N. (2002). Bayesian Analysis of Computer Code Outputs. In Quantitative Methods for Current Environmental Issues, C W Anderson, V Barnett, P C Chatwin, A H El-Shaarawi (editors), 227-243. Springer-Verlag. [Abstract]

• (HE) O'Hagan, A. and Stevens, J. W. (2001). Bayesian assessment of sample size for clinical trials of cost effectiveness. Medical Decision Making 21, 219-230. [Abstract]

• (HE) O'Hagan, A. and Stevens, J. W. (2001). A framework for cost-effectiveness analysis from clinical trial data. Health Economics 10, 302-315. [Abstract]

• (CC) Kennedy, M. and O'Hagan, A. (2001). Bayesian calibration of computer models (with discussion). Journal of the Royal Statistical Society, Series B. 63, 425-464. [Abstract] [Supplementary details, pdf format] [Supplementary details, postscript (if you do not have a postscript viewer you can download Ghostscript and GSview free)]

• (HE) O'Hagan, A, Stevens, J. W. and Montmartin, J. (2001). Bayesian cost effectiveness analysis from clinical trial data. Statistics in Medicine 20, 733-753. [Abstract] [Download WinBUGS program for implementing the method, with original data]

• (EL) Garthwaite, P. and O'Hagan, A. (2000). Quantifying expert opinion in the water industry: an experimental study. The Statistician 49, 455-477. [Abstract]

• (CC) Kennedy, M. and O'Hagan, A. (2000). Predicting the output from a complex computer code when fast approximations are available. Biometrika 87, 1-13. [Abstract]

• Conigliani, C. and O'Hagan, A. (2000). Sensitivity of the fractional Bayes factor to prior distributions. Canadian Journal of Statistics 28, 343-352. [Abstract]

• Conigliani, C. Castro, J. I. and O'Hagan, A. (2000). Bayesian assessment of goodness of fit against nonparametric alternatives. Canadian Journal of Statistics 28, 327-342. [Abstract]

• (HE) O'Hagan, A, Stevens, J. W. and Montmartin, J. (2000). Inference for the C/E Acceptability Curve and C/E Ratio. PharmacoEconomics 17, 339-349. [Abstract]

• Laws, D. J. and O'Hagan, A. (2000). Bayesian inference for rare errors in populations with unequal unit sizes. Applied Statistics 49, 577-590. [Abstract]

• (CC) O'Hagan, A., Kennedy. M. C. and Oakley, J. E. (1999). Uncertainty analysis and other inference tools for complex computer codes (with discussion). In Bayesian Statistics 6, J. M. Bernardo et al (eds.). Oxford University Press, 503-524. [Abstract]

• Ball, F. G., Cai, Y., Kadane, J. B. and O'Hagan, A. (1999). Bayesian inference for ion-channel gating mechanisms directly from single-channel recordings, using Markov chain Monte Carlo. Proceedings of the Royal Society of London A 455, 2879-2932. [Abstract]

• (EL) O'Hagan, A. (1998). Eliciting expert beliefs in substantial practical applications. The Statistician 47, 21-35 (with discussion, pp 55-68). [Abstract]

• Le, H. and O'Hagan, A. (1998). A class of bivariate heavy-tailed distributions. Sankhya B 60, 82-100.

• O'Hagan, A. (1997). The ABLE story: Bayesian asset management in the water industry. In The Practice of Bayesian Analysis, S. French and J. Q. Smith (eds.). Arnold, 173-198. [Abstract]

• O'Hagan, A. (1997). Properties of intrinsic and fractional Bayes factors. Test 6, 101-118. [Abstract]

• (CC) O'Hagan, A. and Haylock, R. G. (1997). Bayesian uncertainty analysis and radiological protection. In Statistics for the Environment 3, Pollution Assessment and Control, 109-128. V. Barnett and K. F. Turkman (eds.). Wiley: Chichester. [Abstract]