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Forward and Backward Recurrence Times and Length Biased Sampling: Age Specific Models

In: Probability, Statistics and Modelling in Public Health

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  • Marvin Zelen

    (Harvard School of Public Health and the Dana-Farber Cancer Institute)

Abstract

Summary Consider a chronic disease process which is beginning to be observed at a point in chronological time. The backward recurrence and forward recurrence times are defined for prevalent cases as the time with disease and the time to leave the disease state respectively, where the reference point is the point in time at which the disease process is being observed. In this setting the incidence of disease affects the recurrence time distributions. In addition, the survival of prevalent cases will tend to be greater than the population with disease due to length biased sampling. A similar problem arises in models for the early detection of disease. In this case the backward recurrence time is how long an individual has had disease before detection and the forward recurrence time is the time gained by early diagnosis; i.e. until the disease becomes clinical by exhibiting signs or symptoms. In these examples the incidence of disease may be age related resulting in a non-stationary process. The resulting recurrence time distributions are derived as well as some generalization of length-biased sampling.

Suggested Citation

  • Marvin Zelen, 2006. "Forward and Backward Recurrence Times and Length Biased Sampling: Age Specific Models," Springer Books, in: Mikhail Nikulin & Daniel Commenges & Catherine Huber (ed.), Probability, Statistics and Modelling in Public Health, pages 1-11, Springer.
  • Handle: RePEc:spr:sprchp:978-0-387-26023-5_1
    DOI: 10.1007/0-387-26023-4_1
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