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 ...
Simon Fraser University

Example 39.9: Conditional Logistic Regression for Matched Pairs Data

In matched case-control studies, conditional logistic regression is used to investigate the relationship between an outcome of being a case or a control and a set of prognostic factors. When each ...
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Logistic Regression Machine Learning Example ¦ Simply Explained

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...
Simon Fraser University

Example 39.1: Stepwise Logistic Regression and Predicted Values

Results of the CTABLE option are shown in Output 39.1.11. Each row of the "Classification Table" corresponds to a cutpoint applied to the predicted probabilities, which is given in the Prob Level ...
ascopubs.org

Tongue image information for prediction esophageal precancerous lesion: A multi-centric logistic regression analysis of esophageal cancer high risk population in China.

Prognostic role of tumor-inflating lymphocytes in gastric cancer: A systematic review and meta-analysis. This is an ASCO Meeting Abstract from the 2017 ASCO Annual Meeting I. This abstract does not ...