Sampling with censored data: a practical guide
Pedro Luiz Ramos, Daniel Camilo Fuentes Guzmán, Alex L. Mota, Daniel Saavedra, Francisco A. Rodrigues, Francisco Louzada
Abstract
In this review, we present a simple guide for researchers to obtain pseudo-random samples with censored data. We focus our attention on the most common types of censored data, such as type I, type II, and random censoring. We discussed the necessary steps to sample pseudo-random values from long-term survival models where an additional cure fraction is informed. For illustrative purposes, these techniques are applied in the Weibull distribution. The algorithms and codes in R are presented, enabling the reproducibility of our study. Finally, we developed an R package that encapsulates these methodologies, providing researchers with practical tools for implementation.