We describe how to conduct a regression analysis for competing risks data. The use of an add-on package for the R statistical software is described, which allows for the estimation of the ...

A framework is developed for the interpretation of regression plots, including plots of the response against selected covariates, residual plots, added-variable plots, and detrended added-variable ...

When multiple variables are associated with a response, the interpretation of a prediction equation is seldom simple.

The main focus of this short course will be the Bayesian aspect of it. That means this is a slightly more advanced course requiring some knowledge of basic probability, regression methods, and the R ...

Peter Frase, opens new tab uses the controversy to rail against non-academic econobloggers, or “wonks”, who parrot the findings of academics: Zach Beauchamp, opens new tab echoes Frase’s ...

I predict you'll find this logistic regression example with R to be helpful for gleaning useful information from common binary classification problems.

Sliced inverse regression (SIR) and an associated chi-squared test for dimension have been introduced as a method for reducing the dimension of regression problems whose predictor variables are normal ...