Nonparametric incidence estimation from prevalent cohort survival data

Marco Carone, Masoud Asgharian, Mei Cheng Wang

Research output: Contribution to journalArticle

Abstract

Incidence is an important epidemiological concept most suitably studied using an incident cohort study. However, data are often collected from the more feasible prevalent cohort study, whereby diseased individuals are recruited through a cross-sectional survey and followed in time. In the absence of temporal trends in survival, we derive an efficient nonparametric estimator of the cumulative incidence based on such data and study its asymptotic properties. Arbitrary calendar time variations in disease incidence are allowed. Age-specific incidence and adjustments for both stratified sampling and temporal variations in survival are also discussed. Simulation results are presented and data from the Canadian Study of Health and Aging are analysed to infer the incidence of dementia in the Canadian elderly population.

Original languageEnglish (US)
Pages (from-to)599-613
Number of pages15
JournalBiometrika
Volume99
Issue number3
DOIs
StatePublished - Sep 1 2012

Keywords

  • Age-specific incidence
  • Cross-sectional sampling
  • Left-truncation
  • Point process
  • Stratification

ASJC Scopus subject areas

  • Statistics and Probability
  • Mathematics(all)
  • Agricultural and Biological Sciences (miscellaneous)
  • Agricultural and Biological Sciences(all)
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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