# Calculate robust standard errors and produce coefficient tables

Source:`R/summ_helpers.R`

`get_robust_se.Rd`

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

## Usage

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

## Arguments

- 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.

## Value

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.