Determining the Probability Distribution and Evaluating Sensitivity and False Positive Rate of a Confounder Detection Method Applied To Logistic Regression

摘要

BackgroundIn epidemiologic studies researchers are often interested in detecting confounding (when a third variable is both associated with and affects associations between the outcome and predictors). Confounder detection methods often compare regression coefficients obtained from “crude” models that exclude the possible confounder(s) and “adjusted” models that include the variable(s). One such method compares the relative difference in effect estimates to a cutoff of 10% with differences of at least 10% providing evidence of confounding.