Is there a way to flip the facet label using small_multiple from the dotwhisker package to have the facet labels on the left-handside and coefficient estimate on the right-hand side? I've seen the solutions to this when using ggplot and facet_wrap or facet_grid, but those aren't working with small_multiple since it does the faceting without those arguments. For simplicity, I'll be using the Dot-and-Whisker Plot Vignette that uses small_multiple as the example.
code used to generate plot:
# Generate a tidy data frame of regression results from six models
m <- list()
ordered_vars <- c("wt", "cyl", "disp", "hp", "gear", "am")
m[[1]] <- lm(mpg ~ wt, data = mtcars)
m123456_df <- m[[1]] %>%
tidy() %>%
by_2sd(mtcars) %>%
mutate(model = "Model 1")
for (i in 2:6) {
m[[i]] <- update(m[[i-1]], paste(". ~ . +", ordered_vars[i]))
m123456_df <- rbind(m123456_df, m[[i]] %>%
tidy() %>%
by_2sd(mtcars) %>%
mutate(model = paste("Model", i)))
}
# Relabel predictors (they will appear as facet labels)
m123456_df <- m123456_df %>%
relabel_predictors(c("(Intercept)" = "Intercept",
wt = "Weight",
cyl = "Cylinders",
disp = "Displacement",
hp = "Horsepower",
gear = "Gears",
am = "Manual"))
# Generate a 'small multiple' plot
small_multiple(m123456_df) +
theme_bw() + ylab("Coefficient Estimate") +
geom_hline(yintercept = 0, colour = "grey60", linetype = 2) +
ggtitle("Predicting Mileage") +
theme(plot.title = element_text(face = "bold"),
legend.position = "none",
axis.text.x = element_text(angle = 60, hjust = 1))
Ideally, I would have the flipped version of this plot with labels on the left and estimates on the right.

