A multivariate cure model for left-censored and right-censored data with application to colorectal cancer screening patterns

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

We develop a multivariate cure survival model to estimate lifetime patterns of colorectal cancer screening. Screening data cover long periods of time, with sparse observations for each person. Some events may occur before the study begins or after the study ends, so the data are both left-censored and right-censored, and some individuals are never screened (the ‘cured’ population). We propose a multivariate parametric cure model that can be used with left-censored and right-censored data. Our model allows for the estimation of the time to screening as well as the average number of times individuals will be screened. We calculate likelihood functions based on the observations for each subject using a distribution that accounts for within-subject correlation and estimate parameters using Markov chain Monte Carlo methods. We apply our methods to the estimation of lifetime colorectal cancer screening behavior in the SEER-Medicare data set.

Original languageEnglish (US)
Pages (from-to)3347-3367
Number of pages21
JournalStatistics in Medicine
Volume35
Issue number19
DOIs
StatePublished - Aug 30 2016

    Fingerprint

Keywords

  • colorectal cancer
  • cure model
  • left-censoring
  • multivariate survival
  • SEER-Medicare

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability

Cite this