Logo image
Imputation methods for doubly censored HIV data
Journal article   Peer reviewed

Imputation methods for doubly censored HIV data

Wei Zhang, Ying Zhang, Kathryn Chaloner and Jack T Stapleton
Journal of statistical computation and simulation, Vol.79(10), pp.1245-1257
10/01/2009
DOI: 10.1080/00949650802255618
PMCID: PMC3034152
PMID: 21304834
url
https://www.ncbi.nlm.nih.gov/pmc/articles/3034152View
Open Access

Abstract

In medical research, it is common to have doubly censored survival data: origin time and event time are both subject to censoring. In this paper, we review simple and probability-based methods that are used to impute interval censored origin time and compare the performance of these methods through extensive simulations in the one-sample problem, two-sample problem and Cox regression model problem. The use of a bootstrap procedure for inference is demonstrated.
logrank test Cox regression model bootstrap Kaplan-Meier curve interval censoring

Details

Metrics

Logo image