将水平线添加到每个面板具有不同截距的“效果图”

Question

I'm using the effects package to plot the effects from an ordinal logistic regression and I'd like to add a different horizontal line (represented the expected baseline probabilities if the predictor has no effect) to the multi-panel plot with a different baseline probability for each panel of the plot.

Here's an example dataset:

# Simulate some data
data = data.frame(predictor_x = rnorm(100, mean = 5, sd = 1),
                    response_y = as.factor(rbinom(100, size = 2, prob = 0.5)))
# Make a model
library(MASS)
model = polr(response_y ~ predictor_x, data = data, Hess= TRUE)
# Plot
library(effects)
p1 = plot(Effects(focal.predictor = "predictor_x", model))
# View
p1
# Try to add a red dashed line for expected probabilities
p1 + abline(h = c(0.25, 0.5, 0.25), col = "red", lty = 3) #failed

Given the plots, I'd like to add a horizontal line at y =.25, for the upper plot, y =.5, for the middle plot, and y =.25, for the lower plot.

Also, I know the + is usually ggplot format so I'm also not sure if that will work either or if you can/how to add more information (like a line) to a saved plot object?

Answer 1

The plot method for Effect objects uses the lattice plotting system, which is neither base R nor ggplot based. However, the ggeffect package can effectively produce the same plot using the ggplot framework, which is a bit easier to work with. In your case, we can do:

library(MASS)
library(effects)
library(ggeffects)

data <- data.frame(predictor_x = rnorm(100, mean = 5, sd = 1),
                  response_y = as.factor(rbinom(100, size = 2, prob = 0.5)))

model <- polr(response_y ~ predictor_x, data = data, Hess= TRUE)

p1 <- plot(ggeffect(model))$predictor_x

p1$facet$params$nrow <- 3

p1 + 
  geom_hline(data = data.frame(response.level = c("X0", "X1", "X2"),
                               y = c(0.25, 0.5, 0.25)),
             aes(yintercept = y), color = "red3", linetype = 2) +
  geom_rug(data = within(data, response.level <- paste0("X", response_y)),
                         aes(x = predictor_x, y = 0.5), sides = "b")