r - How do you extract the coefficient and standard error from the lm() loop?

Question

I was looking at this post on extracting coefficients from a regression loop. I was wondering how I would extract the coefficient and standard error? I thought it would be something like the following, but that appears to not be it:

data <- mtcars[, c("mpg", "cyl", "disp", "hp", "drat", "wt")]
col10 <- names(data)[-1]

lm.test <- vector("list", length(col10))

for(i in seq_along(col10)){
  lm.test[[i]] <- lm(reformulate(col10[i], "mpg"), data = data)
}

lm.test

cfs <- lapply(lm.test, coef[1:2])

question from:https://stackoverflow.com/questions/65909852/how-do-you-extract-the-coefficient-and-standard-error-from-the-lm-loop

Answer 1

Ah, you got the famous "object of type closure is not subsettable" error.

We can use some [[ magic to help us here:

cfs <- lapply(lm.test, `[[`, "coefficients")

The double bracket is a function that extracts a variable name - this effectively loops over the following code:

cf_i <- lm.test[[i]][["coefficients"]]

where i is the number of models in lm.test

EDIT:

More simply,

cfs <- lapply(lm.test, coef)