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Hypothesis Tests for Neyman's Bias in Case-Control Studies.

D M Swanson1,2, C D Anderson3, R A Betensky2

  • 1Oslo Centre for Biostatistics and Epidemiology, Oslo University Hospital, Oslo, NO 0407.

Journal of Applied Statistics
|September 26, 2018
PubMed
Summary

Neyman's bias, a type of survival bias in case-control studies, can distort results when exposure impacts disease and mortality. New hypothesis tests suggest this bias may affect stroke and brain tumor studies.

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Area of Science:

  • Epidemiology
  • Biostatistics

Background:

  • Survival bias is a known issue in case-control studies.
  • Neyman's bias, or prevalence-incidence bias, is a specific form of survival bias.

Purpose of the Study:

  • To define and quantify Neyman's bias in case-control studies.
  • To propose statistical tests for detecting Neyman's bias.
  • To evaluate the presence of Neyman's bias in real-world data.

Main Methods:

  • Developed a formula for the observed odds ratio under Neyman's bias.
  • Compared the derived formula with existing literature.
  • Proposed and applied three hypothesis tests to assess bias.
  • Analyzed datasets on stroke mortality, brain tumors, and atrial fibrillation.
Keywords:
odds ratiosurvival biastruncation

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Main Results:

  • A formula for the biased odds ratio was derived.
  • Evidence of Neyman's bias was found in stroke mortality and brain tumor datasets.
  • No significant evidence of Neyman's bias was detected in the atrial fibrillation dataset.

Conclusions:

  • Neyman's bias can impact case-control study findings.
  • The proposed hypothesis tests can help identify its presence.
  • Further research is warranted to understand the conditions under which this bias is significant.