Newcastle University Research Fellow
Population Health Sciences Institute
Biography
Background
I am a Newcastle University Research Fellow in Biostatistics, interested in methodology for improving the design and analysis of clinical trials. As well as working on developing methodology, I also collaborate on real trials.
I have been at Newcastle University since November 2018. Prior to this I was a Statistician at the MRC Biostatistics Unit, University of Cambridge.
Contact
- Email: michael.grayling@ncl.ac.uk
- Telephone: +44 (0) 191 208 3699
- Address: Population Health Sciences Institute, Baddiley-Clark Building, Richardson Road, Newcastle upon Tyne NE2 4AX, UK
Interests
- Adaptive design
- Early phase oncology trials
- Crossover trials
- Stepped-wedge trials
Education
Wellcome Trust PhD Programme in Mathematical Genomics and Medicine, 2012-16
MRC Biostatistics Unit, University of Cambridge
Systems Biology MSci, 2011-12
University of Cambridge
Mathematics BA (Hons), 2008-11
University of Cambridge
Publications
Quickly discover relevant content by filtering publications.
(2021).
Treatment allocation strategies for umbrella trials in the presence of multiple biomarkers: A comparison of methods.
Pharm Stat 2021; doi:10.1002/pst.2119.
(2020).
PSU4 Value of information for adaptive trials: Proof of concept study in multi-arm multi-stage trials of interventions for the prevention of surgical site infections.
Value Health 2020; 23:S738.
(2020).
Ambulance documentation of stroke symptoms during the UK COVID-19 'Stay at Home' message.
Emerg Med J 2020; 38:83-84.
(2020).
Impact of the COVID-19 lockdown on hangings attended by emergency medical services.
Resuscitation 2020; 157:89-90.
(2020).
Innovative trial approaches in immune-mediated inflammatory diseases: Current use and future potential.
DOI: 10.21203/rs.3.rs-63613/v1.
(2020).
A stochastically curtailed two-arm randomised phase II trial design for binary outcomes.
Pharm Stat 2020; 20:212-28.
(2020).
Increasing power in the analysis of responder endpoints in rheumatology: a software tutorial.
medRxiv 2020.
(2020).
A review of Bayesian perspectives on sample size derivation for confirmatory trials.
arXiv 2020; arXiv:2006.15715.
(2020).
A review of available software for adaptive clinical trial design.
Clin Trials 2020;17:323-31.
(2019).
Sample size re-estimation in crossover trials: Application to the AIM HY-INFORM study.
Trials 2019;20:665.
(2019).
Two-stage adaptive designs for three-treatment bioequivalence studies.
Stat Biopharm Res 2019; 11:360-74.
(2019).
A review of perspectives on the use of randomization in phase II oncology trials.
JNCI: J Natl Cancer I 2019; 111:1255-62.
(2019).
Exact group sequential designs for two-arm experiments with Poisson distributed outcome variables.
Commun Stat Theory.
(2019).
Admissible multiarm stepped‐wedge cluster randomized trial designs.
Stat Med 2019; 38:1103-19.
(2019).
Re-formulating Gehan's design as a flexible two-stage single-arm trial.
BMC Med Res Methodol 2019; 19:22.
(2018).
Calculations involving the multivariate normal and multivariate t distributions with and without truncation.
Stata J 2018; 18:826-43.
(2018).
Blinded and unblinded sample size reestimation in crossover trials balanced for period.
Biom J 2018; 60:917-33.
(2018).
Blinded and unblinded sample size reestimation procedures for stepped-wedge cluster randomized trials.
Biom J 2018; 60:903-16.
(2018).
Group sequential clinical trial designs for normally distributed outcome variables.
Stata J 2018; 18:416-31.
(2018).
An optimised multi-arm multi-stage clinical trial design for unknown variance.
Contemp Clin Trials 2018; 67:116-20.