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Dr Clemence Leyrat

MSc PhD

Associate Professor
in Medical Statistics

Room
G36

LSHTM
Keppel Street
London
WC1E 7HT
United Kingdom

Tel.
+44(0)207 927 2169

After studying cognitive sciences at the University of Bordeaux (France), I obtained a MSc in Biostatistics from the Bordeaux School of Public Health in 2010 and a PhD in 2014 from Paris-Diderot University. My PhD thesis was on the use of propensity score methods for the analysis of cluster randomised trials. During this period, I developed a growing interest in causal inference methods for the analysis of observational data as well as for trial methodology, which has remained my main research area.  After a post-doc at Queen Mary University on the issues of small samples and non-compliance in cluster randomised trials, I joined the department of Medical Statistics at LSHTM in September 2015, to do methodological work on missing data methods in propensity score analysis, working closely with Prof Elizabeth Williamson and Prof James Carpenter. I am also part of the Inequalities in Cancer Outcomes Network (ICON) where I develop and apply causal inference methods to understand cancer inequalities in the UK. 

Affiliations

Department of Non-communicable Disease Epidemiology
Faculty of Epidemiology and Population Health
Department of Medical Statistics

Teaching

I am currently the co-organizer of the module "Advanced Statistica Modelling" for the MSc in Medical Statistics, and involved in the DL module "Cluster Randomised Trials" and the short course "Design & Analysis of Cluster Randomised and Stepped Wedge Trials.

I am an Associate Fellow of the Higher Education Academy.

Research

Currently, I am the PI of a work package within the Horizon 2020 project QUALITOP. This project, led by Prof Delphine Maucourt-Boulch (Hospices Civils de Lyon, France) aims at monitoring multidimensional aspects of quality of life after cancer immunotherapy. As of April 2020, I hold an MRC Skills development fellowship allowing me to investigate how machine learning methods may enhance the design and analysis of cluster randomised trials.

Research Area
Clinical trials
Health inequalities
Statistical methods
Electronic health records
Methodology
Randomised controlled trials
Discipline
Epidemiology
Statistics
Disease and Health Conditions
Cancer
Country
United Kingdom

Selected Publications

Open science saves lives: lessons from the COVID-19 pandemic.
Besançon L; Peiffer-Smadja N; Segalas C; Jiang H; Masuzzo P; Smout C; Billy E; Deforet M; Leyrat C
2021
BMC medical research methodology
Common Methods for Handling Missing Data in Marginal Structural Models: What Works and Why.
Leyrat C; Carpenter JR; Bailly S; Williamson EJ
2020
American journal of epidemiology
Intervention effect estimates in cluster randomized versus individually randomized trials: a meta-epidemiological study
Leyrat C; Caille A; Eldridge S; Kerry S; Dechartres A; Giraudeau B
2018
International Journal of Epidemiology
Cluster randomized trials with a small number of clusters: which analyses should be used? (vol 47, pg 321, 2018)
Leyrat C; Morgan KE; Leurent B; Kahan BC
2018
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY
Propensity score analysis with partially observed covariates: How should multiple imputation be used?
Leyrat C; Seaman SR; White IR; Douglas I; Smeeth L; Kim J; Resche-Rigon M; Carpenter JR; Williamson EJ
2017
Statistical methods in medical research
Timeline cluster: a graphical tool to identify risk of bias in cluster randomised trials.
Caille A; Kerry S; Tavernier E; Leyrat C; Eldridge S; Giraudeau B
2016
BMJ (Clinical research ed)
Propensity score to detect baseline imbalance in cluster randomized trials: the role of the c-statistic.
Leyrat C; Caille A; Foucher Y; Giraudeau B
2016
BMC medical research methodology
A comparison of imputation strategies in cluster randomized trials with missing binary outcomes.
Caille A; Leyrat C; Giraudeau B
2014
Statistical methods in medical research
See more Publications