Running examples in 'broom-Ex.R' failed
The error most likely occurred in:

> ### Name: augment.lm
> ### Title: Augment data with information from a(n) lm object
> ### Aliases: augment.lm
> 
> ### ** Examples
> 
> ## Don't show: 
> if (rlang::is_installed("ggplot2")) (if (getRversion() >= "3.4") withAutoprint else force)({ # examplesIf
+ ## End(Don't show)
+ 
+ library(ggplot2)
+ library(dplyr)
+ 
+ mod <- lm(mpg ~ wt + qsec, data = mtcars)
+ 
+ tidy(mod)
+ glance(mod)
+ 
+ # coefficient plot
+ d <- tidy(mod, conf.int = TRUE)
+ 
+ ggplot(d, aes(estimate, term, xmin = conf.low, xmax = conf.high, height = 0)) +
+   geom_point() +
+   geom_vline(xintercept = 0, lty = 4) +
+   geom_errorbarh()
+ 
+ # aside: There are tidy() and glance() methods for lm.summary objects too.
+ # this can be useful when you want to conserve memory by converting large lm
+ # objects into their leaner summary.lm equivalents.
+ s <- summary(mod)
+ tidy(s, conf.int = TRUE)
+ glance(s)
+ 
+ augment(mod)
+ augment(mod, mtcars, interval = "confidence")
+ 
+ # predict on new data
+ newdata <- mtcars |>
+   head(6) |>
+   mutate(wt = wt + 1)
+ augment(mod, newdata = newdata)
+ 
+ # ggplot2 example where we also construct 95% prediction interval
+ 
+ # simpler bivariate model since we're plotting in 2D
+ mod2 <- lm(mpg ~ wt, data = mtcars)
+ 
+ au <- augment(mod2, newdata = newdata, interval = "prediction")
+ 
+ ggplot(au, aes(wt, mpg)) +
+   geom_point() +
+   geom_line(aes(y = .fitted)) +
+   geom_ribbon(aes(ymin = .lower, ymax = .upper), col = NA, alpha = 0.3)
+ 
+ # predict on new data without outcome variable. Output does not include .resid
+ newdata <- newdata |>
+   select(-mpg)
+ 
+ augment(mod, newdata = newdata)
+ 
+ au <- augment(mod, data = mtcars)
+ 
+ ggplot(au, aes(.hat, .std.resid)) +
+   geom_vline(size = 2, colour = "white", xintercept = 0) +
+   geom_hline(size = 2, colour = "white", yintercept = 0) +
+   geom_point() +
+   geom_smooth(se = FALSE)
+ 
+ plot(mod, which = 6)
+ 
+ ggplot(au, aes(.hat, .cooksd)) +
+   geom_vline(xintercept = 0, colour = NA) +
+   geom_abline(slope = seq(0, 3, by = 0.5), colour = "white") +
+   geom_smooth(se = FALSE) +
+   geom_point()
+ 
+ # column-wise models
+ a <- matrix(rnorm(20), nrow = 10)
+ b <- a + rnorm(length(a))
+ result <- lm(b ~ a)
+ 
+ tidy(result)
+ ## Don't show: 
+ }) # examplesIf
> library(ggplot2)
> library(dplyr)

Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

> mod <- lm(mpg ~ wt + qsec, data = mtcars)
> tidy(mod)
# A tibble: 3 × 5
  term        estimate std.error statistic  p.value
  <chr>          <dbl>     <dbl>     <dbl>    <dbl>
1 (Intercept)   19.7       5.25       3.76 7.65e- 4
2 wt            -5.05      0.484    -10.4  2.52e-11
3 qsec           0.929     0.265      3.51 1.50e- 3
> glance(mod)
Error in ll(object) : could not find function "ll"
Calls: <Anonymous> ... tibble_quos -> eval_tidy -> <Anonymous> -> AIC.default
Execution halted