148 citations · 231 across the 10 of their papers we have counts for
14 papers
Prediction with Missing Data: Target Probabilities and Missingness Mechanisms
Pierre Catoire, Robin Genuer, Cecile Proust-Lima
Conditions ensuring optimal parameter estimation in the presence of missing data are well established in inference, typically relying on the Missing-at-Random (MAR) assumption. In…
Functional principal component analysis as an alternative to mixed-effect models for describing sparse repeated measures in presence of missing data
Corentin Ségalas, Catherine Helmer, Robin Genuer +1
Analyzing longitudinal data in health studies is challenging due to sparse and error-prone measurements, strong within-individual correlation, missing data and various trajectory s…
Random Forests for time-fixed and time-dependent predictors: The DynForest R package
Anthony Devaux, Cécile Proust-Lima, Robin Genuer
The R package DynForest implements random forests for predicting a continuous, a categorical or a (multiple causes) time-to-event outcome based on time-fixed and time-dependent pre…
Random survival forests with multivariate longitudinal endogenous covariates
Anthony Devaux, Catherine Helmer, Robin Genuer +1
Predicting the individual risk of a clinical event using the complete patient history is still a major challenge for personalized medicine. Among the methods developed to compute i…
Individual dynamic prediction of clinical endpoint from large dimensional longitudinal biomarker history: a landmark approach
Anthony Devaux, Robin Genuer, Karine Pérès +1
The individual data collected throughout patient follow-up constitute crucial information for assessing the risk of a clinical event, and eventually for adapting a therapeutic stra…
Fréchet random forests for metric space valued regression with non euclidean predictors
Louis Capitaine, Jérémie Bigot, Rodolphe Thiébaut +1
Random forests are a statistical learning method widely used in many areas of scientific research because of its ability to learn complex relationships between input and output var…