An R function to non-parametric and piecewise analysis of competing risks survival data. - Thomas Filleron; Agnès Laplanche; Jean-Marie Boher; Andrew Kramar (Comput. Methods Programs Biomed., 2010)

Assessment of health status over time by Prevalence and Weighted Prevalence functions: Interface in R. - Bastien Cabarrou; Anaïs Jouin; Jean-Marie Boher; Andrew Kramar; Thomas Filleron (Comput. Methods Programs Biomed., 2015)

Comparison of variable selection methods for high-dimensional survival data with competing events. - Julia Gilhodes; Christophe Zemmour; Soufiane Ajana; Alejandra Martinez; Jean-Pierre Delord; Eve Leconte; Jean-Marie Boher; Thomas Filleron (Comput. Biol. Medicine, 2017)

Focus on an infrequently used quantity in the context of competing risks: The conditional probability function. - Bastien Cabarrou; Florence Dalenc; Eve Leconte; Jean-Marie Boher; Thomas Filleron (Comput. Biol. Medicine, 2018)

Designing phase II clinical trials to target subgroup of interest in a heterogeneous population: A case study using an R package. - Bastien Cabarrou; P. Sfumato; Eve Leconte; Jean-Marie Boher; Thomas Filleron (Comput. Biol. Medicine, 2018)

Goftte: A R package for assessing goodness-of-fit in proportional (sub) distributions hazards regression models. - P. Sfumato; Thomas Filleron; R. Giorgi; Richard J. Cook; Jean-Marie Boher (Comput. Methods Programs Biomed., 2019)

Comparison of Variable Selection Methods for Time-to-Event Data in High-Dimensional Settings. - Julia Gilhodes; Florence Dalenc; Jocelyn Gal; Christophe Zemmour; Eve Leconte; Jean-Marie Boher; Thomas Filleron (Comput. Math. Methods Medicine, 2020)