Length-of-stay Times in Hospital for COVID-19 Patients using the Smoothed Beran's Estimator with Bootstrap Bandwidth Selection: Accepted - May 2024

Rebeca Peláez Suárez; Ricardo Cao; Juan Vilar

Forthcoming

Length-of-stay Times in Hospital for COVID-19 Patients using the Smoothed Beran's Estimator with Bootstrap Bandwidth Selection

Accepted - May 2024

Authors

Rebeca Peláez Suárez Universidad Carlos III de Madrid https://orcid.org/0000-0002-3386-5751
Ricardo Cao Universidade da Coruña https://orcid.org/0000-0001-8304-687X
Juan Vilar Universidade de Coruña

Keywords:

Confidence regions, censored data, conditional survival function, bootstrap, bandwidth selector, confidence regions

Abstract

The survival function of length-of-stay in hospital ward and Intensive Care Unit for COVID-19 patients is studied in this paper. Flexible statistical methods are used to estimate this survival function given relevant covariates such as age, sex, obesity and chronic obstructive pulmonary disease. A doubly-smoothed Beran's estimator has been considered to this aim. The bootstrap method has been used to produce new smoothing parameter selectors and to construct confidence regions for the conditional survival function. Some simulation studies show the good performance of the proposed methods.

Downloads

FP_REVSTAT2024_mai6

Published

2024-05-16

How to Cite

Peláez Suárez, R., Cao, R., & Vilar, J. (2024). Length-of-stay Times in Hospital for COVID-19 Patients using the Smoothed Beran’s Estimator with Bootstrap Bandwidth Selection: Accepted - May 2024. REVSTAT-Statistical Journal. Retrieved from https://revstat.ine.pt/index.php/REVSTAT/article/view/717