Logistic regression is a statistical method used to examine the relationship between a binary outcome variable and one or more explanatory variables. It is a special case of a regression model that ...

Course Topics"Logistic and Poisson Regression," Wednesday, November 5: The fourth LISA mini course focuses on appropriate model building for categorical response data, specifically binary and count ...

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 ...

J. B. Copas, Binary Regression Models for Contaminated Data, Journal of the Royal Statistical Society. Series B (Methodological), Vol. 50, No. 2 (1988), pp. 225-265 ...

The random forest model significantly outperformed all other models, including the logistic regression model that the entire paper focuses on, with an eventual AUC of 0.936 and an accuracy of 0.918.

Article Published: 02 April 2008 Cox proportional hazards models have more statistical power than logistic regression models in cross-sectional genetic association studies Jeroen B van der Net, A ...

A machine learning model may help predict mortality for hospitalized patients with cirrhosis at the time of admission, ...