Methodology research

The methodology group develops, disseminates and implements new statistical methods to improve the efficiency of clinical trials.


 Current areas of research 

  • Basket and Umbrella trials
  • Bayesian methods
  • Cluster-randomised and Stepped Wedge trials
  • Composite endpoints
  • Crossover trial designs
  • Early phase adaptive trials
  • Multi Arm Multi Stage (MAMS) trials
  • Observational study designs
  • Pilot and feasibility studies
  • Platform trials
  • Trials of complex interventions
  • Trials of proportionate interventions
  • Using historical data

 If you are interested in discussing a study that may require novel methods, please contact James Wason.

Selected recent papers

  1. Candlish, J., Teare, M. D., Cohen, J., & Bywater, T. (2019). Statistical design and analysis in trials of proportionate interventions: a systematic review. Trials20(1).
  2. Zheng, Haiyan & V Hampson, Lisa & Wandel, Simon. (2019). A robust Bayesian meta-analytic approach to incorporate animal data into phase I oncology trials. Statistical Methods in Medical Research. 
  3. McMenamin, M., Berglind, A. and Wason, J.M., 2018. Improving the analysis of composite endpoints in rare disease trials. Orphanet journal of rare diseases, 13(1), p.81.
  4. Pallmann, P et al. 2018. Adaptive designs in clinical trials: why use them, and how to run and report them. BMC medicine16(1), p.29.
  5. Grayling, M.J., Wason, J.M. and Mander, A.P., 2018. Group sequential crossover trial designs with strong control of the familywise error rate. Sequential analysis, 37(2), pp.174-203.
  6. Hemming, K., Taljaard, M., McKenzie, J.E., Hooper, R., Copas, A., Thompson, J.A., Dixon-Woods, M., Aldcroft, A., Doussau, A., Grayling, M. and Kristunas, C., 2018. Reporting of stepped wedge cluster randomised trials: extension of the CONSORT 2010 statement with explanation and elaboration. BMJ, 363, p.k1614.
  7. Grayling, M.J., Wason, J.M. and Mander, A.P., 2018. An optimised multi-arm multi-stage clinical trial design for unknown variance. Contemporary clinical trials, 67, pp.116-120.
  8. Candlish, J., Teare, M. D., Dimairo, M., Flight, L., Mandefield, L., & Walters, S. J. (2018). Appropriate statistical methods for analysing partially nested randomised controlled trials with continuous outcomes: a simulation study.. BMC Medical Research Methodology18(1), 105.
  9. Matthews J.N.S., Forbes A.B. Stepped wedge designs: insights from a design of experiments perspective. Stat Med. 2017 Oct 30;36(24):3772-3790.
  10. Cree, I. A., Uttley, L., Buckley Woods, H., Kikuchi, H., Reiman, A., Harnan, S., . . . Shaw, J. (2017). The evidence base for circulating tumour DNA blood-based biomarkers for the early detection of cancer: a systematic mapping review. BMC Cancer17, 697.
  11. Mason, S., Kuczawski, M., Teare, M. D., Stevenson, M., Goodacre, S., Ramlakhan, S., . . . Rothwell, J. (2017). AHEAD Study: an observational study of the management of anticoagulated patients who suffer head injury. BMJ Open7(1).
  12. Wason, J.M., Abraham, J.E., Baird, R.D., Gournaris, I., Vallier, A.L., Brenton, J.D., Earl, H.M. and Mander, A.P., 2015. A Bayesian adaptive design for biomarker trials with linked treatments. British journal of cancer, 113(5), p.699.
  13. Villar, S.S., Wason, J. and Bowden, J., 2015. Response‐adaptive randomization for multi‐arm clinical trials using the forward looking Gittins index rule. Biometrics, 71(4), pp.969-978.
  14. Matthews J.N.S., Badi N.H., 2015. Inconsistent treatment estimates from mis‐specified logistic regression analyses of randomized trials. Stat. Med. 2015,34 2681–2694.