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 regression model, preferably of class lm
or glm
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()]).
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
.
The data used to fit the model. Default is to just get the
model.frame
from model
.
You may provide the variance-covariance matrix yourself and this function will just calculate standard errors, etc. based on that. Default is 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.