Using purrr:map2 to perform regression where the predictor and the criterion are stored in different objects

for the purposes of this question, let’s create the following setup:

mtcars %>% 
  group_split(carb) %>% 
  map(select, mpg) -> criterion

mtcars %>% 
  group_split(carb) %>% 
  map(select, qsec) -> predictor

This code will create two lists of length 6. What I want to do is to perform 6 linear regressions within each of these 6 groups. I read about the map2 function and I thought that the code should look like this:

map2(criterion, predictor, lm(criterion ~ predictor))

But that doesn’t seem to work. So in which way could this be done?

>Solution :

simplify2array (you need a list of vectors, not a list of data frames) and use a lambda-function with ~:

map2(simplify2array(criterion), simplify2array(predictor), ~ lm(.x ~ .y))