Score tests in a generalized linear model with surrogate covariates

We consider generalized linear models where a predictor is measured with error. The efficient score test for the effect of that predictor depends on the regression of the true predictor on its observed surrogate. Using validation data, we estimate the regression by nonparametric techniques. The resulting semiparametric score test is shown to be nearly asymptotically efficient.