Bias in Scientific Studies

Delimitation

Bias must be distinguished from fraud, oversights, misunderstandings, and nonsense arithmetic. It must further be distinguished from the field of statistical pitfalls, illusions, and paradoxes, though each of these, when unrecognized, may bias perceptions and recommendations.

The classical borderline between random error and bias is sometimes fuzzy. The label “bias” is often used about poor data recording, regardless of whether it will affect conclusions and, if so, how. Moreover, blunt procedures (imprecise measurements) may delay the recognition of a health hazard, or benefit, and in that sense pure randomness is itself “biased” against public interests.

Recognition of Bias

Just as, while there is no ...