Robust estimation
standard_error_robust()
, ci_robust()
and p_value_robust()
attempt to return indices based on robust estimation of the variance-covariance
matrix, using the packages sandwich and clubSandwich.
standard_error_robust( model, vcov_estimation = "HC", vcov_type = NULL, vcov_args = NULL, ... ) p_value_robust( model, vcov_estimation = "HC", vcov_type = NULL, vcov_args = NULL, ... ) ci_robust( model, ci = 0.95, vcov_estimation = "HC", vcov_type = NULL, vcov_args = NULL, ... )
model |
A model. |
vcov_estimation |
String, indicating the suffix of the |
vcov_type |
Character vector, specifying the estimation type for the
robust covariance matrix estimation (see |
vcov_args |
List of named vectors, used as additional arguments that
are passed down to the sandwich-function specified in |
... |
Arguments passed to or from other methods. For |
ci |
Confidence Interval (CI) level. Default to 0.95 (95%). |
A data frame.
These functions rely on the sandwich or clubSandwich package
(the latter if vcov_estimation = "CR"
for cluster-robust standard errors)
and will thus only work for those models supported by those packages.
Working examples cam be found in this vignette.
if (require("sandwich", quietly = TRUE)) { # robust standard errors, calling sandwich::vcovHC(type="HC3") by default model <- lm(Petal.Length ~ Sepal.Length * Species, data = iris) standard_error_robust(model) } ## Not run: if (require("clubSandwich", quietly = TRUE)) { # cluster-robust standard errors, using clubSandwich iris$cluster <- factor(rep(LETTERS[1:8], length.out = nrow(iris))) standard_error_robust( model, vcov_type = "CR2", vcov_args = list(cluster = iris$cluster) ) } ## End(Not run)
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