Introduction
A common difficulty in regression modeling is to figure out which input variables should be included. One tool at our disposal is the added-variable plot. Given an existing model, the added-variable plot lets us visualize the improvement we would get by adding one more variable of our choosing. This idea is described nicely in

A function for displaying add-variable curves can be found in R's car package, among other places. That package is the support software for An R Companion to Applied Regression, and has other useful functions for regression modeling.

Simulated Data To illustrate the added-variable graphs, I'll use simulated data. Simulations are useful, because when we build the relationship between variables by hand, we know what the answer is when we start. Then we can check the actual answer versus the regression model.

library(tidyverse) library(broom) add_names <-function(x…

*A Modern Approach to Regression with R*by Simon J. Sheather, pages 162-166.A function for displaying add-variable curves can be found in R's car package, among other places. That package is the support software for An R Companion to Applied Regression, and has other useful functions for regression modeling.

Simulated Data To illustrate the added-variable graphs, I'll use simulated data. Simulations are useful, because when we build the relationship between variables by hand, we know what the answer is when we start. Then we can check the actual answer versus the regression model.

library(tidyverse) library(broom) add_names <-function(x…