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 ...

When the dependent variable has two responses, the parameter estimates from the CATMOD procedure are the same as those from a logistic regression program such ... some commonly used models for the ...

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 ...

"Logistic and Poisson Regression," Wednesday, November 5: The fourth LISA mini course focuses on appropriate model building for categorical response data, specifically binary and count data. The most ...

As the coronavirus disease 2019 (COVID-19) pandemic has spread across the world, vast amounts of bioinformatics data ... the logistic regression model, 3,386 samples were used for the analysis ...