Nonparametric incidence estimation from prevalent cohort survival data
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. Copyright 2012, Oxford University Press.
Year of publication: |
2012
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Authors: | Carone, Marco ; Asgharian, Masoud ; Wang, Mei-Cheng |
Published in: |
Biometrika. - Biometrika Trust, ISSN 0006-3444. - Vol. 99.2012, 3, p. 599-613
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Publisher: |
Biometrika Trust |
Saved in:
Online Resource
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