Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population ...

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 ...

Dr. James McCaffrey of Microsoft Research says the main advantage of scikit is that it's easy to use (even though most classes have many constructor parameters). Logistic regression is a machine ...

As the coronavirus disease 2019 (COVID-19) pandemic has spread across the world, vast amounts of bioinformatics data have been created and analyzed, and logistic regression models have been key to ...

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 ...

Objective This study aimed to determine the characteristics of acute poisoning patients. Design This was a prospective cohort study. Setting The study was conducted for 1 year (1 July 2023 to 30 June ...