title: Robust estimation for the Cox regression model based on trimming.
abstract: We propose a robust Cox regression model with outliers. The model is fit by trimming the smallest contributions to the partial likelihood. To do so, we implement a Metropolis-type maximization routine, and show its convergence to a global optimum. We discuss global robustness properties of the approach, which is illustrated and compared through simulations. We finally fit the model on an original and on a benchmark data set.
authors: Department of Public Health and Infectious Diseases, Sapienza - University of Rome, Italy.
authors: Alessio
authors: A
authors: Farcomeni
authors: Sara
authors: S
authors: Viviani
mesh_terms: D001699:Biometry; D006501:Hepatic Encephalopathy / Q000453:epidemiology; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D008875:Middle Aged; D016016:Proportional Hazards Models; D011471:Prostatic Neoplasms / Q000453:epidemiology