How to extract tidy output from many single-variable models using purrr broom

Question

Consider data frame that comprises a binary outcome column (y), and multiple independent predictor columns (x1, x2, x3...)

I want to run many single-variable logistic regression models (e.g. y ~ x1, y ~ x2, y ~ x3), and extract the exponentiated coefficients (odds ratios), 95% confidence intervals and p-values for each model into rows of a data frame/tibble. 

I am trying to find a solution by using a combination of purrr and broom.

Working from the example in the referenced question:

library(tidyverse)
library(broom)

df <- mtcars

df %>%
 names() %>%
 paste('am~',.) %>%
 map(~glm(as.formula(.x), data= df, family = "binomial"))

Answer 1

You can try this solution:

filter_starwars <- function(...) {
  F <- quos(...)
  filter(starwars, !!!F)
}

filter_starwars(species == 'Human', homeworld %in% c('Tatooine', 'Alderaan'), height > 175)
# # A tibble: 7 × 13
#                  name height  mass  hair_color skin_color eye_color birth_year
#                 <chr>  <int> <dbl>       <chr>      <chr>     <chr>      <dbl>
# 1         Darth Vader    202   136        none      white    yellow       41.9
# 2           Owen Lars    178   120 brown, grey      light      blue       52.0
# 3   Biggs Darklighter    183    84       black      light     brown       24.0
# 4    Anakin Skywalker    188    84       blond       fair      blue       41.9
# 5         Cliegg Lars    183    NA       brown       fair      blue       82.0
# 6 Bail Prestor Organa    191    NA       black        tan     brown       67.0
# 7     Raymus Antilles    188    79       brown      light     brown         NA
# # ... with 6 more variables: gender <chr>, homeworld <chr>, species <chr>,
# #   films <list>, vehicles <list>, starships <list>