I'm having trouble creating an interaction effect plot. There is probably something fairly simple I don't yet know how to do. I'm pretty new to R and ggplot. My reprex is below. Your insight is greatly appreciated!
The data is from UCLA and I'm also adapting their example for my purposes here.
library(here)
library(emmeans)
library(tidyverse)
dat <- read.csv("https://stats.idre.ucla.edu/wp-content/uploads/2019/03/exercise.csv")
Convert prog into factor variable
dat$prog <- factor(dat$prog, labels = c("jog","swim","read"))
The model
contcat <- lm(loss ~ hours * prog, data=dat)
summary(contcat)
I create mylist with certain points on hours and the two categories in prog that I want to contrast.
(mylist <- list(hours = seq(0, 4, .5), prog=c("jog","read")))
I then pass the object contcat into the emmeans. I request that predicted values of every combination of hours and prog be specified in at=mylist and store the output into an object called emcontcat.
emcontcat <- emmeans(contcat, ~ hours * prog, at=mylist)
I use emmip to output a set of values using plotit=FALSE.
contcatdat <- emmip(contcat, prog ~ hours, at = mylist, CIs=TRUE, plotit=FALSE)
The output object is fed to ggplot. The interaction effect is plotted along with CI bands.
ggplot(data=contcatdat, aes(x=hours, y=yvar, color=prog)) +
geom_line() +
geom_ribbon(aes(ymax=UCL, aymin=LCL, fill=prog), alpha=0.4)
The plot looks like this:
But overlapping CIs do not always correspond to the portions of the lines where there is no significant differences in predicted values. I want to add hashed lines for the portions of the lines where there is no significant difference in predicted values. This figure below
shows the kind of figure I'm trying to create. (The figure is from a paper by Trenton Mize (2019) found here at Fig. 14.)
To get the simple effect (i.e., difference of two predicted values), I pass emcontcat into a function called contrast where we can request "pairwise" differences (or simple effects). P-values are given for jog - read at each level of hours that was specified in mylist.
contrast(emcontcat, "pairwise", by="hours")
The output:
Where I am having trouble is how to incorporate the simple effect (i.e., the parts of hours where jog - read are significantly different or not) into ggplot as hashed or solid portions of the lines like the Mize 2019 figure.
