Drawing a regression line with interaction in ggplot2

With the ggeffects package, drawing a regression line with interaction in ggplot2 can be achieved using the ggpredict() function.

library(tidyverse)
library(ggeffects)

#Generate an example dataset for reproduciblity:
set.seed(42)
example_data = 
  data.frame(treatment   = as.factor(c(rep("t1", 50), rep("t2", 50))),
             time        = rep(1:50, 2), 
             error       = rnorm(100, 0, 1))                      %>% 
  mutate(    slope       = ifelse(treatment == "t1", -0.2, -0.3)) %>% 
  mutate(    measurement = 2.5 + time * slope + error)          

#Linear model that I want to display in my plot: 
model = lm(measurement ~ time:treatment, data = example_data)
summary(model)

g <- ggpredict(model, terms=c("time", "treatment")) 

plot(g)

The ggpredict() function produces a modified tibble, on which you can call plot() to generate a plot with superposed lines.

Since the result of plot(g) is a ggplot object, you can modify it in the expected ways (e.g., adding a facet):

plot(g) + facet_wrap(~group)