Plot the impact for each variable in linear regression?

Question

I want to create a plot like below for a lm model calculated using R.

Is there a simple way of doing it?

The plot above was collected here in this page.

Answer 1

Package {caret} offers a convenient method varImp: Example:

library(caret)
my_model <- lm(mpg ~ disp + cyl, data = mtcars)

## > varImp(my_model)
##
##       Overall
## disp 2.006696
## cyl  2.229809

For different measures of variable importance see ?varImp. Feed values into your plotting library of choice.

Extra: {ggstatsplot} calculates and plots a host of model stats for a plethora of model objects. This includes hypotheses about regression coefficients, for which method ggcoefstats() might serve your purpose (remember to scale predictor variables for meaningful comparison of coefficients though).