STOCHASTIC COVARIATES IN BINARY REGRESSION

Year 2004, Volume: 33 , 97 - 109, 01.01.2004

Evrim Oral Süleyman Günay

Abstract

Binary regression has many medical applications. In applying the tech-

nique, the tradition is to assume the risk factor $X$ as a non-stochastic

variable. In most situations, however, $X$ is stochastic. In this study,

we discuss the case when $X$ is stochastic in nature, which is more re-

alistic from a practical point of view than $X$ being non-stochastic. We

show that our solutions are much more precise than those obtained by

treating $X$ as non-stochastic when, in fact, it is stochastic.

Keywords

Binary regression, Robustness, Skew family, Symmetric family, Modified Maximum Likelihood Estimator

References

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