Sampling with censored data: a practical guide

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-ter...

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Bibliographic Details
Published in:Journal of statistical computation and simulation 2024-12, Vol.94 (18), p.4072-4106
Main Authors: Ramos, Pedro L., Guzman, Daniel C. F., Mota, Alex L., Saavedra, Daniel A., Rodrigues, Francisco A., Louzada, Francisco
Format: Article
Language:English
Subjects:
Algorithms
Censored data
Censored data (mathematics)
cure fraction
Pseudorandom
sampling
simulation
Weibull distribution
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Summary: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.
ISSN:0094-9655
1563-5163
DOI:10.1080/00949655.2024.2409379