Related Experiment Videos
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
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.
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.
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.