In this article, an exact conditional goodness-of-fit test for the logistic regression model with grouped binomial response data is proposed. Two efficient algorithms are presented for carrying out ...

A new study investigated how logistic regression model training affects performance, and which features are best to include when examining datasets from individuals suffering from COVID-19.

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 ...

Logistic regression was used to develop a risk prediction model using the FIT result and screening data: age, sex and previous screening history.

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.

The data doctor continues his exploration of Python-based machine learning techniques, explaining binary classification using logistic regression, which he likes for its simplicity.

By comparison, classical statistical models such as logistic regression (LR) rely on selection of risk factors, often on the basis of a priori knowledge. Although ML techniques have achieved recent ...

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...