This is a preview. Log in through your library . Abstract This article considers semiparametric estimation in logistic regression with missing covariates. In a ...

A class of conditional logistic regression models for clustered binary data is considered. This includes the polychotomous logistic model of Rosner (1984) as a special case. Properties such as the ...

Many complex disease traits are observed to be associated with single nucleotide polymorphism (SNP) interactions. In testing small-scale SNP–SNP interactions, variable selection procedures in logistic ...

Patients with no exposure to anthracyclines served as the reference group. Magnitude of risk is expressed as odds ratio, which was obtained using conditional logistic regression adjusting for age at ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...