ON ERRORS-IN-VARIABLES FOR BINARY REGRESSION-MODELS
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We consider binary regression models when some of the predictors are measured with error. For normal measurement errors, structural maximum likelihood estimates are considered. We show that if the measurement error is large, the usual estimate of the probability of the event in question can be substantially in error, especially for high risk groups. In the situation of large measurement error, we investigate a conditional maximum likelihood estimator and its properties. 1984 Biometrika Trust.
author list (cited authors)
CARROLL, R. J., SPIEGELMAN, C. H., LAN, K., BAILEY, K. T., & ABBOTT, R. D.
complete list of authors
CARROLL, RJ||SPIEGELMAN, CH||LAN, KKG||BAILEY, KT||ABBOTT, RD