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Ascertainment Bias

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Ascertainment bias is the systematic difference in the identification of individuals in a study, or the data collected. It results in a distortion in measuring the true frequency of a phenomenon in the population.

“When the chance of a person being sampled, or feature being observed, depends on some background factor, for example when people in the treated arm of a randomized trial get closer supervision than the control group.”

— David Spiegelhalter, “The Art of Statistics, Learning from Data