THE EFFECT OF MISCLASSIFICATION IN THE PRESENCE OF COVARIATES

The effects of misclassification on analyses involving a discrete covariate are examined and it is shown that biased and unbiased mis classification will tend to distort the degree of heterogeneity in the measure of association being considered.

Abstract

The effects of misclassification on analyses involving a discrete covariate are examined. The following points are illustrated: 1) Analogous to the 2 X 2 table case, unbiased misclassification of the study exposure leads to reduction in the observed strength of the association of exposure with disease. 2) Both biased and unbiased misclassification will tend to distort the degree of heterogeneity in the measure of association being considered. 3) Misclassification of a confounder leads to a partial loss of ability to control confounding.