Parametric models for combined failure time data from an incident cohort study and a prevalent cohort study with follow-up

Int J Biostat. 2020 Oct 12;17(2):283-293. doi: 10.1515/ijb-2020-0042.

Abstract

A classical problem in survival analysis is to estimate the failure time distribution from right-censored observations obtained from an incident cohort study. Frequently, however, failure time data comprise two independent samples, one from an incident cohort study and the other from a prevalent cohort study with follow-up, which is known to produce length-biased observed failure times. There are drawbacks to each of these two types of study when viewed separately. We address two main questions here: (i) Can our statistical inference be enhanced by combining data from an incident cohort study with data from a prevalent cohort study with follow-up? (ii) What statistical methods are appropriate for these combined data? The theory we develop to address these questions is based on a parametrically defined failure time distribution and is supported by simulations. We apply our methods to estimate the duration of hospital stays.

Keywords: combined cohort; maximum likelihood estimation; survival analysis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cohort Studies
  • Follow-Up Studies
  • Humans
  • Incidence
  • Models, Statistical*
  • Survival Analysis