On errors-in-variables for binary regression models

@article{Carroll1984OnEF,
  title={On errors-in-variables for binary regression models},
  author={Raymond J. Carroll and Clifford H. Spiegelman and K. K. Gordon Lan and Kent Bailey and Robert D Abbott},
  journal={Biometrika},
  year={1984},
  volume={71},
  pages={19-25}
}
SUMMARY 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. 

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