Get a named variance-covariance matrix from a model object (internal function)
get_vcov(model, ...)# S3 method for default
get_vcov(model, vcov = NULL, ...)
# S3 method for afex_aov
get_vcov(model, vcov = NULL, ...)
# S3 method for glimML
get_vcov(model, vcov = NULL, ...)
# S3 method for biglm
get_vcov(model, vcov = NULL, ...)
# S3 method for brmsfit
get_vcov(model, vcov = NULL, ...)
# S3 method for gamlss
get_vcov(model, ...)
# S3 method for mhurdle
get_vcov(model, ...)
# S3 method for orm
get_vcov(model, vcov = NULL, ...)
# S3 method for scam
get_vcov(model, vcov = NULL, ...)
A named square matrix of variance and covariances. The names must match the coefficient names.
Model object
Additional arguments are passed to the predict()
method
supplied by the modeling package.These arguments are particularly useful
for mixed-effects or bayesian models (see the online vignettes on the
marginaleffects
website). Available arguments can vary from model to
model, depending on the range of supported arguments by each modeling
package. See the "Model-Specific Arguments" section of the
?marginaleffects
documentation for a non-exhaustive list of available
arguments.
Type of uncertainty estimates to report (e.g., for robust standard errors). Acceptable values:
FALSE: Do not compute standard errors. This can speed up computation considerably.
TRUE: Unit-level standard errors using the default vcov(model)
variance-covariance matrix.
String which indicates the kind of uncertainty estimates to return.
Heteroskedasticity-consistent: "HC"
, "HC0"
, "HC1"
, "HC2"
, "HC3"
, "HC4"
, "HC4m"
, "HC5"
. See ?sandwich::vcovHC
Heteroskedasticity and autocorrelation consistent: "HAC"
Mixed-Models degrees of freedom: "satterthwaite", "kenward-roger"
Other: "NeweyWest"
, "KernHAC"
, "OPG"
. See the sandwich
package documentation.
One-sided formula which indicates the name of cluster variables (e.g., ~unit_id
). This formula is passed to the cluster
argument of the sandwich::vcovCL
function.
Square covariance matrix
Function which returns a covariance matrix (e.g., stats::vcov(model)
)