Extracting the T Statistic from a function in R - r

Question

I have this function that I got from a textbook that runs a couple of linear regressions and then saves the P-Value for each regression.
I would also like to save the T-Statistic as well but I am having a hard time finding the right syntax to enter for the select function.
Here is the current function.
models <- lapply(paste(factors, ' ~ a + b + c + d + e + f + g + h+ j -',factors),
function(f){ lm(as.formula(f), data = df) %>% # Call lm(.)
summary() %>% # Gather the output
"$"(coef) %>% # Keep only the coefs
data.frame() %>% # Convert to dataframe
filter(rownames(.) == "(Intercept)") %>% # Keep only the Intercept
dplyr::select(Estimate,`Pr...t..`)}) # Keep the coef & p-value
I know that I have to change the very last part of the function: dplyr::select(Estimate,`Pr...t..`) but after all my research and trial and error I am still stuck.
Here is a reproducible example using the mtcars data.
library(dplyr)
df <- mtcars
df <- df %>%
select(1,2,3,4,5,6,7)
factors <- c("mpg", "cyl", "disp", "hp", "drat", "wt")
models <- lapply(paste(factors, ' ~ mpg + cyl + disp + hp + drat + wt -',factors),
function(f){ lm(as.formula(f), data = df) %>% # Call lm(.)
summary() %>% # Gather the output
"$"(coef) %>% # Keep only the coefs
data.frame() %>% # Convert to dataframe
filter(rownames(.) == "(Intercept)") %>% # Keep only the Intercept
dplyr::select(Estimate,`Pr...t..`)} # Keep the coef & p-value
)
final <- matrix(unlist(models), ncol = 2, byrow = T) %>% # Switch from list to dataframe
data.frame(row.names = factors

Answer 1

Your example works for me. You can make this a little bit more "tidy" as follows:
library(broom)
sumfun <- function(f) {
lm(as.formula(f), data = df) %>%
tidy() %>%
filter(term == "(Intercept)") %>%
dplyr::select(estimate, p.value)
}
pp <- paste(factors, ' ~ mpg + cyl + disp + hp + drat + wt -',factors)
names(pp) <- factors
final <- purrr::map_dfr(pp, sumfun, .id = "factor")