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 ...
Nature

A comparison of Cox and logistic regression for use in genome-wide association studies of cohort and case-cohort design

Logistic regression is often used instead of Cox regression to analyse genome-wide association studies (GWAS) of single-nucleotide polymorphisms (SNPs) and disease outcomes with cohort and case-cohort ...
JSTOR Daily

Categorical Data Analysis: Some Reflections on the Log Linear Model and Logistic Regression. Part II: Data Analysis

Imrey, Koch, Stokes and collaborators (1981) have reviewed the literature of log linear and logistic categorical data modelling, and presented a matrix formulation of log linear models parallel to the ...
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 ...
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.