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Related Experiment Videos

Neyman's bias re-visited.

Gerry Hill1, James Connelly, Réjean Hébert

  • 1Department of Community Health and Epidemiology, Queen's University, Abramsky Hall, Arch Street, Kingston K7L 3N6, Ontario, Canada. hill1930@hotmail.com

Journal of Clinical Epidemiology
|May 28, 2003
PubMed
Summary
This summary is machine-generated.

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Neyman

Area of Science:

  • Epidemiology
  • Biostatistics

Background:

  • Case-control studies with prevalent cases can yield spurious associations if risk factors influence survival.
  • Neyman's bias, a potential confounding factor, was described without considering competing risks.

Purpose of the Study:

  • To illustrate Neyman's bias using a compartment model.
  • To determine the conditions under which Neyman's bias explains apparent associations in epidemiological studies.

Main Methods:

  • Utilized a compartment model to simulate disease progression and survival.
  • Analyzed the impact of a dichotomous risk factor on disease-specific mortality.

Main Results:

  • Neyman's bias explains apparent associations only when the risk factor affects mortality from the disease under study.

Related Experiment Videos

  • The influence of the risk factor on mortality from other causes is irrelevant to this specific bias.

    • Conclusions:

    • Neyman's bias is relevant for irreversible noncommunicable diseases and dichotomous risk factors.
    • The apparent protective effect of smoking in Alzheimer's disease serves as an illustrative example.