How to plot glht() confidence intervals with ggplot()?

Question

Using glht() from the multcomp package, one can calculate the confidence intervals of different treatments, like so ( source ):

Simultaneous Confidence Intervals

Multiple Comparisons of Means: Tukey Contrasts

Fit: lm(formula = Years ~ Attr, data = MockJury)

Quantile = 2.3749

95% family-wise confidence level
Linear Hypotheses:
                                Estimate  lwr       upr
Average - Beautiful ==      0   -0.3596   -2.2968   1.5775
Unattractive - Beautiful == 0    1.4775   -0.4729   3.4278
Unattractive - Average ==   0    1.8371   -0.1257   3.7999

These intervals can then be visualized using plot() :

Is it possible to plot these intervals using ggplot() (for consistency and aesthetics)? If so, how?

If not, is there a workaround to make the output resemble a ggplot() chart?

Answer 1

If you convert the output of confint to a data frame, then you can directly plot the output in ggplot2. Here's an approach (using a glht example from the help file) that uses the tidy function from broom to convert confint() output to a data frame suitable for plotting:

library(multcomp)
library(tidyverse)
library(broom)

lmod <- lm(Fertility ~ ., data = swiss)

m = glht(lmod, linfct = c("Agriculture = 0",
                          "Examination = 0",
                          "Education = 0",
                          "Catholic = 0",
                          "Infant.Mortality = 0"))

confint(m) %>% 
  tidy %>% 
  ggplot(aes(lhs, y=estimate, ymin=conf.low, ymax=conf.high)) +
    geom_hline(yintercept=0, linetype="11", colour="grey60") +
    geom_errorbar(width=0.1) + 
    geom_point() +
    coord_flip() +
    theme_classic()

UPDATE: In response to the comment...

Curved ends for the confidence intervals

I'm not sure of an easy way to add curved ends to the errorbars, by you can come close by using geom_segment and arrows with a shallow arrowhead angle.

confint(m) %>% 
  tidy %>% 
  ggplot(aes(x=lhs, y=estimate)) +
  geom_hline(yintercept=0, linetype="11", colour="grey60") +
  geom_segment(aes(xend=lhs, y=conf.low, yend=conf.high), size=0.4, 
               arrow=arrow(ends="both", length=unit(0.05, "inches"), angle=70)) + 
  geom_point() +
  coord_flip() +
  theme_classic()

lhs ordering

In terms of ordering, lhs will be ordered alphabetically unless it is converted to a factor with a specific order. For example, below we order by the value of estimate .

confint(m) %>% 
  tidy %>% 
  arrange(estimate) %>% 
  mutate(lhs = factor(lhs, levels=unique(lhs))) %>%   # unique() returns values in the order they first appear in the data
  ggplot(aes(x=lhs, y=estimate)) +
  geom_hline(yintercept=0, linetype="11", colour="grey60") +
  geom_segment(aes(xend=lhs, y=conf.low, yend=conf.high), size=0.4, 
               arrow=arrow(ends="both", length=unit(0.05, "inches"), angle=70)) + 
  geom_point() +
  coord_flip() +
  theme_classic()