Clémence Leyrat

Propensity score analysis with partially observed covariates: How should multiple imputation be used?

Clémence Leyrat, Shaun R. Seaman, Ian R. White et al. · Statistical Methods in Medical Research · 2017 · 252 citations · Full text

Public Health, Biostatistics, Causal Inference +16

Cluster randomized trials with a small number of clusters: which analyses should be used?

Clémence Leyrat, Katy E. Morgan, Baptiste Leurent et al. · International Journal of Epidemiology · 2017 · 240 citations · Full text

Public Health, Biostatistics, Epidemiologic Methods +11

Increased risk of type I errors in cluster randomised trials with small or medium numbers of clusters: a review, reanalysis, and simulation study

Brennan C Kahan, Gordon Forbes, Yunus Ali et al. · Trials · 2016 · 187 citations · Full text

Public Health, Biostatistics, Clinical Epidemiology +13

Reflection on modern methods: trial emulation in the presence of immortal-time bias. Assessing the benefit of major surgery for elderly lung cancer patients using observational data

Camille Maringe, Sara Benítez Majano, Aimilia Exarchakou et al. · International Journal of Epidemiology · 2020 · 187 citations · Full text

Public Health, Biostatistics, Geriatric Medicine +17

G-computation, propensity score-based methods, and targeted maximum likelihood estimator for causal inference with different covariates sets: a comparative simulation study

Arthur Chatton, Florent Le Borgne, Clémence Leyrat et al. · Scientific Reports · 2020 · 127 citations · Full text

Public Health, Biostatistics, Causal Inference +15