Interaction Model

Let’s look at the interaction model in multiple regression.

Let’s now quantify the relationship of our outcome variable $y$ and the two explanatory variables using one type of multiple regression model known as an interaction model.

We’ll write out the equation of the two regression lines using the values from a regression table. Before we do this, however, let’s go over a brief refresher of regression when we have a categorical explanatory variable $x.$

Recall how we fit a regression model for countries’ life expectancies as a function of which continent the country was in. In other words, we had a numerical outcome variable $y =$ lifeExp and a categorical explanatory variable $x =$ continent, which had five levels—Africa, the Americas, Asia, Europe, and Oceania. Let’s redisplay the regression table:

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Getting Started with Data in R

Data Visualization

Data Wrangling

Data Importing and “Tidy” Data

Basic Regression

Multiple Regression

Statistical Inference with the infer Package

Bootstrapping and Confidence Intervals

Hypothesis Testing

Inference for Regression

Tell a Story with Data

Appendix

Interaction Model