Email Address: email@example.com
Thomas recently joined the BSU as a Programme Leader in the DART theme. Thomas has been Professor of Statistics at University of Lancaster, where he has led several substantial research projects and is head of Medical Statistics. His work has focused on developing and evaluating novel statistical methods for clinical and pre-clinical studies. These methods are adapted for specific applications to ensure they can be used in the pharmaceutical industry and also in public sector research institutions.
Thomas is in a transitional period, continuing to work with University of Lancaster, before taking on his role with the Unit full time later in the year.
Thomas will lead this continuously evolving research theme into a new era, developing new streams of clinical trials tackling current public health challenges, including COVID-19.
- Programme Leader, DART, MRC Biostatistics Unit, University of Cambridge, since April 2020
- Professor of Statistics, Department of Mathematics and Statistics - Lancaster University, since Aug 2015
- Director, Medical and Pharmaceutical Statistics Research Unit, since Jan 2014
- Reader, Department of Mathematics and Statistics - Lancaster University, Aug 2013 - July 2015
- Deputy director, Medical and Pharmaceutical Statistics Research Unit, Aug 2010 - Dec 2013
- Lecturer, Department of Mathematics and Statistics - Lancaster University, June 2007 - July 2013
- Assistant Professor, Department of Mathematics - Cleveland State University, Aug 2006 − May 2007
- Ph.D. in Statistics, Aug 2006, University of South Carolina Dissertation: “Maximum kernel likelihood estimation” Advisor: Dr. R. Webster West
- M.S. in Statistics, May 2003, Johannes Kepler University, Linz, Austria Thesis: “Verfahren für Prognoseprobleme der Energiewirtschaft” (Methods for the prediction problems in the energy industry) Advisor: Dr. Helga Wagner
Selected recent publications
- Whitehead J, Desai Y, Jaki T (accepted) Estimation of treatment effects following a sequential trial of multiple treatments. Statistics in Medicine.
- Dimairo M, Pallmann P, Wason J, Susan Todd S, Jaki T, Julious SA, Mander AP, Weir CJ, Koenig F, Walton MK, Nicholl JP, Coates E, Biggs K, Hamasaki T, Proschan MA, Scott JA, Ando Y, Hind D, Altman DG (accepted) The Adaptive designs CONSORT Extension (ACE) Statement: A checklist with explanation and elaboration guideline for reporting randomised trials that use an adaptive design. BMJ - British Medical Journal.
- Dean NE, Gsell P-S, Brookmeyer R, Crawford FW, Donnelly CA, Ellenberg SS, Fleming T, Halloran ME, Horby P, Jaki T, Krause PR, Longini IM, Mulangu S, Muyembe-Tamfum J-J, Nason MC, Smith PG, Wang R, Restrepo AMH,De Gruttola V (2020) Accumulating Evidence from Randomized Clinical Trials across Outbreaks. New England Journal of Medicine. 382(14):1366-1369.
- Wan F, Titman A, Jaki T. (2019) Subgroup analysis of treatment effects for misclassified biomarkers with time-to-event data. Journal of the Royal Statistical Society - Series C. 68(5):1447-1463.
- Jaki T, Pallmann P, Magirr D (2019) R Package MAMS for Designing Multi-Arm Multi-Stage Clinical Trials. Journal of Statistical Software. 88(4).
- Pallmann P, Bedding AW, Choodari-Oskooei B, Munyaradzi Dimairo M, Flight L, Hampson LV, Holmes J, Mander AP, Odondi L, R Sydes MR, Villar SS, Wason JMS, Weir CJ, Wheeler GM, Yap C, Jaki T. (2018) Adaptive designs in clinical trials: why use them, and how to run and report them. BMC Medicine. 16:29