A researcher notices that patients who survive a disease are more likely to be enrolled in a long-term follow-up study than those who die early. This is an example of:

• A Berkson's bias
• B Volunteer bias
• C Neyman (incidence-prevalence) bias ✓
• D Information bias

Explanation

Neyman bias (also called incidence-prevalence bias or survival bias) occurs when studying prevalent rather than incident cases — patients who die shortly after diagnosis are excluded, and only survivors (who may have milder disease or a different exposure profile) are captured. This distorts the association between exposure and disease. Berkson's bias occurs in hospital-based studies due to differential admission rates; volunteer bias relates to self-selection.

Reference: Park's Textbook of Preventive and Social Medicine, 27th ed.

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