get_robust_se: Calculate robust standard errors and produce coefficient tables

Description

This function wraps around several sandwich and lmtest functions to calculate robust standard errors and returns them in a useful format.

get_robust_se(
  model,
  type = "HC3",
  cluster = NULL,
  data = model.frame(model),
  vcov = NULL
)

A list with the following:

coefs: a coefficient table with the estimates, standard errors, t-statistics, and p-values from lmtest.
ses: The standard errors from coefs.
ts: The t-statistics from coefs.
ps: The p-values from coefs.
type: The argument to robust.
use_cluster: TRUE or FALSE indicator of whether clusters were used.
cluster: The clusters or name of cluster variable used, if any.
vcov: The robust variance-covariance matrix.

model: A regression model, preferably of class lm or glm
type: One of "HC3", "const", "HC", "HC0", "HC1", "HC2", "HC4", "HC4m", "HC5". See sandwich::vcovHC() for some more details on these choices. Note that some of these do not work for clustered standard errors (see sandwich::vcovCL()).
cluster: If you want clustered standard errors, either a string naming the column in data that represents the clusters or a vector of clusters that is the same length as the number of rows in data.
data: The data used to fit the model. Default is to just get the model.frame from model.
vcov: You may provide the variance-covariance matrix yourself and this function will just calculate standard errors, etc. based on that. Default is NULL.