CODEWITHSUNDEEP
rpurrrbroom
Peter MacPherson
Peter MacPherson

Reputation: 733

Tidy output from many single-variable models using purrr, broom

I have a dataframe that comprises of a binary outcome column (y), and multiple independent predictor columns (x1, x2, x3...).

I would like 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 dataframe/tibble. It seems to me that a solution should be possible using a combination of purrr and broom.

This question is similar, but I can't work out the next steps of:

  1. extracting only the values I need and
  2. tidying into a dataframe/tibble.

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"))

Upvotes: 2

Views: 1301

Answers (1)

Peter MacPherson
Peter MacPherson

Reputation: 733

After sleeping on it, the solution occurred to me. Requires the use of map_df to run each model, and tidy to extract the values from each model.

Hopefully this will be useful for others:

library(tidyverse)
library(broom)

df <- mtcars

output <- df %>%
  select(-am) %>%
  names() %>%
  paste('am~',.) %>%
  map_df(~tidy(glm(as.formula(.x), 
               data= df, 
               family = "binomial"), 
               conf.int=TRUE, 
               exponentiate=TRUE)) %>%
  filter(term !="(Intercept)")

Upvotes: 4

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