Below is a reproducible example similar to what I'm doing with another data set. Notice at the very end I use guide_legend() twice to fix the legend title since I'm using both fill and color scales. Is there a more efficient way to do that?
Thanks in advance!
# load some sample data data(iris) # fit a silly model with interaction m <- lm(Sepal.Length ~ Sepal.Width * Species, data = iris) # Create data for effect plot to visualize interaction library(ggeffects) eff_out <- ggpredict(m, terms = c("Sepal.Width", "Species")) # create effect plot using eff_out ggplot(eff_out, aes(x = x, y = predicted, color = group)) + geom_line() + geom_ribbon(aes(ymin = conf.low, ymax = conf.high, fill = group), alpha = 1/5) + scale_x_continuous("Sepal Width") + scale_y_continuous("Sepal Length") + guides(fill = guide_legend(title="Species"), color = guide_legend(title="Species"))