4.3 Article

Imputation methods for doubly censored HIV data

Journal

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
Volume 79, Issue 10, Pages 1245-1257

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/00949650802255618

Keywords

bootstrap; Cox regression model; interval censoring; Kaplan-Meier curve; logrank test

Funding

  1. University of Iowa Graduate College
  2. NIH/NIAID [R01 058740]
  3. NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES [R01AI058740] Funding Source: NIH RePORTER
  4. NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [T32GM077973] Funding Source: NIH RePORTER

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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.

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