JSTOR Daily

Conditional Logistic Regression Models for Correlated Binary Data

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 ...
JSTOR Daily

Mixed conditional logistic regression for habitat selection studies

1. Resource selection functions (RSFs) are becoming a dominant tool in habitat selection studies.RSF coefficients can be estimated with unconditional (standard) and conditional logistic regressions.
News Medical

Researchers investigate COVID-19 data with logistic regression model training

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 ...
technologynetworks

Logistic Regression

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 ...
ascopubs.org

A Comparison of Logistic Regression Against Machine Learning Algorithms for Gastric Cancer Risk Prediction Within Real-World Clinical Data Streams

TRAIL Score: A Simple Model to Predict Immunochemotherapy Tolerability in Patients With Diffuse Large B-Cell Lymphoma We trained models using logistic regression (LR) and four commonly used ML ...