Random or non-differential misclassification of disease biases the effect measure towards the null and underestimates the effect measure but does not introduce bias.

Non-random or differential misclassification is a systematic error that biases the effect measures away from the null exaggerating or underestimating the effect measure. Positive association may become negative and negative associations association may become positive.

Misclassification bias is classified as information bias, detection bias, and proto-pathic bias.

Information bias is systematic incorrect measurement on response due to questionnaire defects, observer errors, respondent errors, instrument errors, diagnostic errors, and exposure mis-specification.

Detection bias arises when disease or exposure are sought more vigorously in one comparison more than the other group.

Protopathic bias arises when early signs of disease cause a change in behaviour with regard to the risk factor.

Misclassification bias can be prevented by using double-blind techniques to decrease observer and respondent bias.

Treatment of misclassification bias is by the probabilistic approach or measurement of inter-rater variation.