| Open science saves lives: lessons from the COVID-19 pandemic L Besançon, N Peiffer-Smadja, C Segalas, H Jiang, P Masuzzo, C Smout, ... BMC Medical Research Methodology 21 (1), 117, 2021 | 295 | 2021 |
| A hypothesis testing procedure for random changepoint mixed models C Segalas, H Amieva, H Jacqmin‐Gadda Statistics in medicine 38 (20), 3791-3803, 2019 | 12 | 2019 |
| Propensity score matching after multiple imputation when a confounder has missing data C Ségalas, C Leyrat, JR Carpenter, E Williamson Statistics in Medicine 42 (7), 1082-1095, 2023 | 5 | 2023 |
| A curvilinear bivariate random changepoint model to assess temporal order of markers C Segalas, C Helmer, H Jacqmin-Gadda Statistical methods in medical research 29 (9), 2481-2492, 2020 | 5 | 2020 |
| Re: Subramanian and Kumar. Vaccination rates and COVID-19 cases M Mulot, C Segalas, C Leyrat, L Besançon European journal of epidemiology 36 (12), 1243-1244, 2021 | 4 | 2021 |
| Long term evolution of renal function in essential hypertensive patients with no baseline proteinuria P Gosse, C Segalas, S Rubin, R Boulestreau, H Jacqmin-Gadda, ... Journal of human hypertension 34 (8), 560-567, 2020 | 3 | 2020 |
| Do machine learning methods lead to similar individualized treatment rules? A comparison study on real data F Bouvier, E Peyrot, A Balendran, C Ségalas, I Roberts, F Petit, R Porcher Statistics in Medicine 43 (11), 2043-2061, 2024 | 1 | 2024 |
| Functional Principal Component Analysis as an Alternative to Mixed‐Effect Models for Describing Sparse Repeated Measures in Presence of Missing Data C Ségalas, C Helmer, R Genuer, C Proust‐Lima Statistics in Medicine, 2024 | | 2024 |
| Strong instrumental variables biased propensity scores in comparative effectiveness research: A case study in oncology NH Thurin, J Jové, R Lassalle, M Rouyer, S Lamarque, P Bosco-Levy, ... Journal of Clinical Epidemiology 155, 31-38, 2023 | | 2023 |
| Has COVID-19 been the making of Open Science? L Besançon, C Segalas, C Leyrat Impact of Social Sciences Blog, 2021 | | 2021 |
| Pulling Unmeasured Confounding Out by your Bootstraps: Too Good to be True? C Segalas, C Leyrat, E Williamson Journal of Statistical Research 55 (2), 293-297, 2021 | | 2021 |
| A semi-latent class model for estimating the time of differentiation of cognitive decline between cases and controls C Segalas12, H Jacqmin-Gadda 35th International Workshop on Statistical Modelling, 422, 2020 | | 2020 |
| Inference for random changepoint models: application to pre-dementia cognitive decline C Segalas Université de Bordeaux, 2019 | | 2019 |
Clémence LeyratLondon School of Hygiene and Tropical MedicineVerified email at lshtm.ac.uk
