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\noindent Statistica Sinica {\bf 13}(2003), 111-127
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\centerline{\large\bf ESTIMATION OF A LOGISTIC REGRESSION MODEL}
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\centerline{\large\bf WITH MISMEASURED OBSERVATIONS}
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\centerline{K. F. Cheng and H. M. Hsueh}
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\centerline{\it National Central University and National Chengchi University}
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\begin{quotation}
\noindent {\it Abstract:}
We consider the estimation problem of a logistic regression model. We assume
the response observations and covariate values are both subject to measurement
errors. We discuss some parametric and  semiparametric estimation  methods
using mismeasured observations with validation data and derive their asypmtotic
distributions. Our results are extentions of some well known results in the
literature. Comparisons of the asymptotic covariance matrices of the studied
estimators are made, and some lower and upper bounds for the asymptotic
relative efficiencies are given to show the advantages of the semiparametric
method. Some  simulation results also show the method performs well.\par
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\noindent {\it Key words and phrases:}
Kernel estimation, estimated likelihood, logistic
regression, measurement error, misclassification.
\end{quotation}
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