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

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 ...

A solid coverage of the most important parts of the theory and application of regression models, and generalised linear models. Multiple regression and regression diagnostics. Generalised linear ...

Regression analysis is a quantitative tool that is easy to use and can provide valuable information on financial analysis and forecasting.

Although monotonic regression in one dimension is well studied, the question remains whether one can find computationally feasible generalizations to multiple dimensions. Here, we propose a ...

We accommodate the longitudinal nature of the multiple outcomes with a unique extension of the nested random effects logistic model with an autoregressive structure to include drop-out and baseline ...