Andrew Copas, Professor of Trials in Global Health
Andrew joined the Unit in 2006 after previously working elsewhere at UCL from 1994, including several years in the Department of Statistical Science. In 1999 he gained a PhD on missing data and selection bias.
Andrew works on statistical methodology relating to the design and analysis of trials. His major research interest is cluster randomised trials, in particular (i) optimising the design of trials with baseline data and stepped wedge trials, and (ii) defining estimands to answer the research question. He also has interests in noninferiority trials, repeated measurements, and missing data.
Andrew is collaborating with Prof Karla Hemming (Birmingham) on an MRC-NIHR award on Developing guidance for design and conduct of cluster randomised trials. He recently collaborated with Dr Rebecca Walwyn (PI) at the University of Leeds, on an NIHR funded project to address the design and analysis of 'open cohort' cluster randomised trials in which individuals may join and leave clusters during the trial.
Andrew also works within UCL, in the Institute for Global Health, where he is Director of the Centre for Pragmatic Global Health Trials. He is the lead statistician for several ongoing trials in the UK and overseas, many of which are cluster randomised, including parallel group, cross-over and stepped wedge designs.
Andrew has published over 300 peer reviewed articles and is associate editor for the journals Statistics in Medicine and Sexually Transmitted Infections. He is also a Clarivate Highly Cited Researcher (2022).
Selected publications
Kahan, B. C., Li, F., Copas, A. J., & Harhay, M. O. (2023). Estimands in cluster-randomized trials: choosing analyses that answer the right question. Int J Epidemiol, 52(1), 107-118. doi:1093/ije/dyac131
Caille, A., Taljaard, M., Le Vilain-Abraham, F., Le Moigne, A., Copas, A. J., Tubach, F., & Dechartres, A. (2022). Recruitment and implementation challenges were common in stepped-wedge cluster randomized trials: Results from a methodological review. J Clin Epidemiol, 148, 93-103. doi:1016/j.jclinepi.2022.04.024
Clements, M. N., White, I. R., Copas, A. J., Cornelius, V., Cro, S., Dunn, D. T., . . . Walker, A. S. (2022). Improving clinical trial interpretation with ACCEPT analyses. NEJM Evid, 1(8). doi:1056/EVIDctw2200018
Copas, A. J., & Hooper, R. (2021). Optimal design of cluster randomized trials allowing unequal allocation of clusters and unequal cluster size between arms. Stat Med, 40(25), 5474-5486. doi:1002/sim.9135
South, A., Joharatnam-Hogan, N., Purvis, C., James, E. C., Diaz-Montana, C., Cragg, W. J., . . . Copas, A. J. (2021). Testing approaches to sharing trial results with participants: The Show RESPECT cluster randomised, factorial, mixed methods trial. PLoS Med, 18(10), e1003798. doi:1371/journal.pmed.1003798
Research Interests
- Cluster randomised trials with baseline data
- Stepped wedge trials
- Estimands for cluster randomised trials
- ‘Open cohort’ cluster randomised trials
- Noninferiority trials