Imputation methods for doubly censored HIV data

Wei Zhang, Ying Zhang, Kathryn Chaloner, Jack T. Stapleton

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1245-1257
Number of pages13
JournalJournal of Statistical Computation and Simulation
Issue number10
StatePublished - Oct 2009
Externally publishedYes


  • Bootstrap
  • Cox regression model
  • Interval censoring
  • Kaplan-Meier curve
  • Logrank test

ASJC Scopus subject areas

  • Statistics and Probability
  • Modeling and Simulation
  • Statistics, Probability and Uncertainty
  • Applied Mathematics


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