Professor Richard Hooper

Profile

I joined QMUL in 2010 having worked previously as a biostatistician at Cambridge University, King’s College London, Imperial College London, and also for a short time with the Government Statistical Service in the Department of Health. I am Professor of Medical Statistics and Deputy Centre Lead at the Centre for Evaluation & Methods, and interim Director of the Pragmatic Clinical Trials Unit, as well as Institutional Co-Lead at QMUL for the NIHR Research Support Service (RSS) Hub at Imperial College London & Partners. In 2019 I was awarded a Senior Fellowship with The Healthcare Improvement Studies (THIS) Institute, and am now a member of their alumni community.

Research

Research Interests:

My research programme is aimed at driving innovation in the design of randomised evaluations of health interventions and quality improvement programmes, including stepped wedge trials and other novel approaches to clustered trials. To find out more about stepped wedge trials visit my Stepped Wedgehog website. My work has appeared in the BMJ, the International Journal of Epidemiology, the Journal of Clinical Epidemiology, Statistics in Medicine, and Statistical Methods in Medical Research. I have given invited talks at international conferences of the International Society for Clinical Biostatistics, Royal Statistical Society, and Society for Clinical Trials.

Publications

Outstanding Publications: 

Hooper R. Key concepts in epidemiology: stepped wedge trials. J Clin Epi 2021;137:159-162

Hooper R, Eldridge S. Cutting edge or blunt instrument: how to decide if a stepped wedge design is right for you. BMJ Quality Safety 2021;30:245-250

Hooper R, Copas A. Stepped wedge trials with continuous recruitment require new ways of thinking. J Clin Epidemiol 2019;116:161-166

Hooper R, Teerenstra S, de Hoop E, Eldridge S. Sample size calculation for stepped wedge and other longitudinal cluster randomised trials. Stat Med 2016;35:4718-4728

Hooper R, Bourke L. Cluster randomised trials with repeated cross-sections: alternatives to parallel group designs. BMJ 2015;350:h2925

Supervision

• Nadine Marlin (NIHR Doctoral Fellowship): Statistical methods for modelling complex associations in meta-analysis

• Mary Venn (CovidSurg Collaborative): Studies of harm from surgery