Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...

Beside the model, the other input into a regression analysis is some relevant sample data, consisting of the observed values of the dependent and explanatory variables for a sample of members of the ...

The standard linear regression model does not apply when the effect of one explanatory variable on the dependent variable depends on the value of another explanatory variable. In this case, the ...

Journal of the Royal Statistical Society. Series D (The Statistician), Vol. 47, No. 2 (1998), pp. 377-383 (7 pages) In medical and social surveys a large number of multiply correlated explanatory ...

The purpose of this tutorial is to continue our exploration of regression by constructing linear models with two or more explanatory variables. This is an extension of Lesson 9. I will start with a ...

Economists develop economic models to explain consistently recurring relationships. Their models link one or more economic variables to other economic variables (see “Economic Models,” p. 8). For ...

The application of Cox proportional hazards (CoxPH) models to survival data and the derivation of hazard ratio (HR) are well established. Although nonlinear, tree-based machine learning (ML) models ...