Function to create bootstrap confidence intervals using infer

You need the in dev version of dplyr to use group_map

#library(devtools)
#install_github("tidyverse/dplyr")

Creating bootstrap confidence intervals

library(tidyverse)
library(tidymodels)

calculate_ci_boot <- function(d, x, ...) {
  x <- ensym(x)
  
  d_estimate <- d %>%
    group_by(...) %>%
    group_map(
      ~ .x %>% 
        specify(expr(!!x ~ NULL)) %>% 
        calculate(stat = "mean") 
    )
  
  d_ci <- d %>%
    group_by(...) %>%
    group_map(
      ~ .x %>% 
        specify(expr(!!x ~ NULL)) %>% 
        generate(reps = 10000, type = "bootstrap") %>% 
        calculate(stat = "mean") %>% 
        get_confidence_interval() 
    )
  
  left_join(d_estimate, d_ci)
}

mtcars_boot_ci <- mtcars %>% 
  calculate_ci_boot(mpg, gear, am) %>% 
  rename(estimate = stat, conf.low = `2.5%`, conf.high = `97.5%`) %>% 
  mutate(type = "boot")

## Joining, by = c("gear", "am")

Creating t-test confidence intervals

calculate_ci <- function(d, x, ...) {
  d %>%
    group_by(...) %>%
    group_map(~t.test(.x %>% pull(!!enquo(x)), conf.int = TRUE) %>% tidy()) 
}

mtcars_ttest_ci <- mtcars %>% 
  calculate_ci(mpg, gear, am) %>% 
  mutate(type = "t-test")

Comparing bootstrap and t-test confidence intervals

mtcars_boot_ci %>% 
  bind_rows(mtcars_ttest_ci) %>% 
  ggplot(aes(x = gear, y = estimate, ymin = conf.low, ymax = conf.high, 
             color = type)) +
  facet_wrap(~ am) +
  geom_pointrange(position = position_dodge(.2))