THE BIAS OF ESTIMATING EQUATIONS WITH APPLICATION TO THE ERROR RATE OF LOGISTIC DISCRIMINATION

The logistic regression classification method uses parameter estimates that are the solution of an estimating equation. This article derives a convenient expression for the bias of a vector estimator defined by estimating equations. The expression and the results of O'Neill are u sed to derive the bias and the error or misclassification rate of logi stic regression classification in two examples where the assumed model for logistic regression does not hold. Logistic regression classifica tion is found to be very robust for the departures considered.