How to plot interaction effects of treatments (in R, using ggpubr)
Task
When there are multiple treatment conditions with multiple levels and you wish to undertsand the interaction effects of each of them, a plot can be useful. How can we create the right kind of plot for that situation?
- How to create basic plots
- How to add details to a plot
- How to create a histogram
- How to create a box (and whisker) plot
- How to change axes, ticks, and scale in a plot
- How to create bivariate plots to compare groups
Solution
The solution below uses an example dataset about the teeth of 10 guinea pigs at three Vitamin C dosage levels (in mg) with two delivery methods (orange juice vs. ascorbic acid). (See how to quickly load some sample data.)
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df <- ToothGrowth
To plot the interaction effects among tooth length, supplement, and dosage, we can use the ggline function in the ggpubr package. You can change the x and color inputs below depending on your goals, but the y input should always be the dependent variable.
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# install.packages("ggpubr") # If you have not already installed it
library(ggpubr)
ggline(df, x="dose", y="len", color="supp", add=c("mean"))
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Loading required package: ggplot2
Looking at the output, we first see that there is an interaction effect because the two supp lines intersect. We also see that there is a difference in length when giving 0.5mg and 1mg dosage of either of the two delivery methods. However, there is barely any difference between the delivery methods when the dosage level is 2mg.
Content last modified on 24 July 2023.
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Contributed by Krtin Juneja (KJUNEJA@falcon.bentley.edu)