Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

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 ...

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

Li, Y. and Liu, J. (2025) An Accessible Predictive Model for Alzheimer’s Disease Based on Cognitive and Neuropathological ...

This is a preview. Log in through your library . Abstract Logistic regression models are commonly used to study the association between a binary response variable and an exposure variable. Besides the ...

The following table details the results of a series of statistical models predicting various measures related to people’s attitudes toward electric vehicles from a set of explanatory variables, or ...