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I've been trying follow the approach set out by Hadley Wickham for running multiple models in a nested data frame as per https://r4ds.had.co.nz/many-models.html

I've managed to write this code below to create the multiple linear models:

#create nested data frame
by_clin_grp <- df_long %>%
  group_by(clin_risk) %>%
  nest()
#create a function to run the linear models
model <- function(df){
  lm(outcome ~ age + sex + clin_sub_grp, data =df)
#run the models
by_clin_grp <- by_clin_grp %>%
  mutate(model = map(data,model))
#unnest the models using the broom package 
by_clin_grp_unnest <- by_clin_grp %>%
  mutate(tidy = map(model, broom::tidy))%>%
  unnest(tidy)
However, I need to add confidence intervals around my regression estimates. It seems like I should be able to add them using broom::tidy as per the help page but I'm unable to work out how to specify this correctly in the code above?
You have to specify the relevant arguments inside map. There are two possibilities:
by_clin_grp_unnest <- by_clin_grp %>%
  mutate(tidy = map(model, ~broom::tidy(.x, conf.int = TRUE, conf.level = 0.99)))%>%
  unnest(tidy)
by_clin_grp_unnest <- by_clin_grp %>%
  mutate(tidy = map(model, broom::tidy, conf.int = TRUE, conf.level = 0.99)) %>%
  unnest(tidy)
Both are equivalent just differ in syntax
        
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