Survival curve estimation for informatively coarsened discrete event-time data

Michelle Shardell, Daniel O. Scharfstein, Samuel A. Bozzette

Research output: Contribution to journalArticlepeer-review

Abstract

Interval-censored, or more generally, coarsened event-time data arise when study participants are observed at irregular time periods and experience the event of interest in between study observations. Such data are often analysed assuming non-informative censoring, which can produce biased results if the assumption is wrong. This paper extends the standard approach for estimating survivor functions to allow informatively interval-censored data by incorporating various assumptions about the censoring mechanism into the model. We include a Bayesian extension in which final estimates are produced by mixing over a distribution of assumed censoring mechanisms. We illustrate these methods with a natural history study of HIV-infected individuals using assumptions elicited from an AIDS expert.

Original languageEnglish (US)
Pages (from-to)2184-2202
Number of pages19
JournalStatistics in Medicine
Volume26
Issue number10
DOIs
StatePublished - May 10 2007

Keywords

  • Coarsened at random
  • Informative censoring
  • Interval censoring
  • Sensitivity analysis
  • Survival

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability

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