Removing table components in stargazer - r

Question

I am putting together tables using stargazer and presenting them in a HTML file using RMarkdown. Reproducible code to create the image is pasted below.
I would like to remove the stars and standard errors associated with the constant ("Alpha" in the image below).
I understand that I can manually overwrite the table components but is there a way that I can automatically retain stars and SE for everything but the alpha row? To re-write everything into character vectors seems a little cumbersome.
Code:
library(tidyverse)
library(stargazer)
mdl1 <- lm(mpg~wt, mtcars)
mdl2 <- lm(mpg~disp, mtcars)
mdls <- list(mdl1,mdl2)
column.labels <- c('model 1',
'model 2')
covariate.labels <- c('Beta 1',
'Beta 2',
'Alpha')
keep.stat <- c('n')
stargazer(mdls, type = 'html',
column.labels = column.labels,
covariate.labels = covariate.labels,
column.sep.width = "10pt",
dep.var.labels.include = F,
keep.stat = keep.stat)

Answer 1

In a comment you asked if an alternative to stargazer could help you
with this. The answer is “yes”, the modelsummary
package can do this
relatively easily. (Disclaimer: I am the maintainer.)
I say “relatively” because what you are asking is very idiosyncratic, so
I don’t think you should expect it to work out of the box in any
package. But here’s an example.
First, we start with a basic table with nice labels:
library(modelsummary)
library(broom)
models <- list(
lm(mpg ~ wt + hp, mtcars),
lm(mpg ~ disp + hp, mtcars))
coef_map <- c(
"wt" = "Weight",
"disp" = "Displacement",
"hp" = "Horse Power")
modelsummary(models, stars = TRUE, coef_map = coef_map)
The Customizing Existing Models
section
of the documentation explains that modelsummary allows you to
overwrite any estimate (coef, standard error, p value, etc.) by defining
a new function called tidy_custom.CLASSNAME, where CLASSNAME refers
to the type of model object you are trying to summarize.
In our example above, we summarize lm models:
class(models[[1]])
## [1] "lm"
Therefore, our customizing function will be called tidy_custom.lm. Say
your goal is to remove the standard errors, stars, and p values from the
table, but only for the variable hp. What we can do is overwrite the
estimates with NA (please refer to the docs linked above for a
detailed explanation):
tidy_custom.lm <- function(model) {
out <- tidy(model)
out$p.value[out$term == "hp"] <- NA
out$std.error[out$term == "hp"] <- NA
return(out)
}
modelsummary(models, stars = TRUE, coef_map = coef_map)