coefficient plot

R code of the ggplot2 example

library(ggplot2)
library(carData)

## Linear model of the 2008-09 nine-month salaries of US professors; each
## coefficient with its 95% interval, other variables held constant.
model <- lm(salary ~ rank + discipline + yrs.since.phd + yrs.service + sex, data = Salaries)
terms <- c(rankAssocProf = "Associate vs assistant professor", rankProf = "Full vs assistant professor",
           disciplineB = "Applied vs theoretical department", yrs.since.phd = "Each year since the PhD",
           yrs.service = "Each year of service", sexMale = "Men vs women")
coefs <- data.frame(term = terms[names(coef(model))[-1]], estimate = coef(model)[-1],
                    confint(model)[-1, ], check.names = FALSE)
names(coefs)[3:4] <- c("low", "high")
coefs$term <- factor(coefs$term, levels = rev(terms))

p <- ggplot(coefs, aes(x = estimate, y = term)) +
  geom_vline(xintercept = 0, colour = "#535353", linewidth = 0.4, linetype = "dashed") +
  geom_errorbar(aes(xmin = low, xmax = high), width = 0, orientation = "y", colour = "#9b2367",
                linewidth = 0.6) +
  geom_point(size = 2, colour = "#9b2367") +
  scale_x_continuous(labels = \(x) paste0("$", lex_number(x))) +
  labs(title = "Full professors earn about $45 000 more than assistant\nprofessors; the $4 800 men–women gap is not significant",
       subtitle = "Salary differences in a linear model of 397 professors at one US college, 2008–09",
       x = "Difference in nine-month salary", y = NULL,
       caption = "Data: Fox & Weisberg 2019, via the carData R package") +
  theme_lex_viz(grid = "x", arrows = "")