S. Faye Williamson

S. Faye Williamson

Research Associate

Population Health Sciences Institute

Biography

Background

I joined the PHSI Biostatistics Research Group in January 2021 as a Research Associate working with Professor James Wason. I am interested in the development of novel clinical trial designs and will be working on a mixture of methodological research (in the area of precision medicine) and applying new methods in practice.

Qualifications:

PhD Statistics and Operational Research, STOR-i Centre for Doctoral Training, Lancaster University

MRes Statistics and Operational Research, STOR-i Centre for Doctoral Training, Lancaster University

BSc Mathematics, Department of Mathematics and Statistics, Lancaster University

Research

My research interests include, but are not limited to, the following areas:

  1. The use of response-adaptive randomisation in clinical trials;
  2. Personalising treatment allocation in clinical trials;
  3. Overcoming barriers which prevent the application of novel trial designs in practice.

Contact

Publications

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Svetlana Cherlin, Theophile Bigirumurame, Michael J Grayling, Jérémie Nsengimana, Luke Ouma, Aida Santaolalla, Fang Wan, S Faye Williamson, James MS Wason (2023). Utilising high-dimensional data in randomised clinical trials: A review of methods and practice. Research Methods in Medicine & Health Sciences.

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Martin Law, Dominique-Laurent Couturier, Babak Choodari-Oskooei, Phillip Crout, Carrol Gamble, Peter Jacko, Philip Pallmann, Mark Pilling, David S. Robertson, Michael Robling, Matthew R. Sydes, Sofía S. Villar, James Wason, Graham Wheeler, S. Faye Williamson, Christina Yap, Thomas Jaki (2023). Medicines and Healthcare products Regulatory Agency’s “Consultation on proposals for legislative changes for clinical trials”: a response from the Trials Methodology Research Partnership Adaptive Designs Working Group, with a focus on data sharing. Trials.

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S. Faye Williamson, Michael J. Grayling, Adrian P. Mander, Nurulamin M. Noor, Joshua S. Savage, Christina Yap, James M. S. Wason (2022). Subgroup analyses in randomized controlled trials frequently categorized continuous subgroup information. Journal of Clinical Epidemiology.

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Kevin J. Wilson, S. Faye Williamson, A. Joy Allen, Cameron J. Williams, Thomas P. Hellyer, B. Clare Lendrem (2022). Bayesian sample size determination for diagnostic accuracy studies. Statistics in Medicine.

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S. Faye Williamson, Peter Jacko, Thomas Jaki (2021). Generalisations of a Bayesian decision-theoretic randomisation procedure and the impact of delayed responses. Computational Statistics & Data Analysis.

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Stallard N, Hampson L, Benda N, Brannath W, Burnett T, Friede T, Kimani PK, Koenig F, Krisam J, Mozgunov P, Posch M, Wason J, Wassmer G, Whitehead J, Williamson SF, Zohar S, Jaki T (2020). Efficient adaptive designs for clinical trials of interventions for COVID-19. Stat Biopharm Res 2020; 12:483-97.

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Williamson SF (2020). Bayesian bandit models for the design of clinical trials. PhD Thesis, Lancaster University 2020; DOI:10.17635/lancaster/thesis/917.

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Williamson SF, Villar SS (2019). A response‐adaptive randomization procedure for multi‐armed clinical trials with normally distributed outcomes. Biometrics 2019; 79(1):197-209.

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Williamson SF, Jacko P, Villar SS, Jaki T (2016). A Bayesian adaptive design for clinical trials in rare diseases. Comput Stat Data An 2016; 113:136-153.

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