standard_error() attempts to return standard errors of model
parameters.
standard_error(model, ...)
# Default S3 method
standard_error(
model,
effects = "fixed",
component = "all",
vcov = NULL,
vcov_args = NULL,
verbose = TRUE,
...
)
# S3 method for class 'factor'
standard_error(model, force = FALSE, verbose = TRUE, ...)A model.
Arguments passed to or from other methods.
Should standard errors for fixed effects ("fixed"), random
effects ("random"), or both ("all") be returned? Only applies
to mixed models. May be abbreviated. When standard errors for random
effects are requested, for each grouping factor a list of standard errors
(per group level) for random intercepts and slopes is returned.
Model component for which standard errors should be shown.
See the documentation for your object's class in model_parameters() or
p_value() for further details.
Variance-covariance matrix used to compute uncertainty estimates (e.g., for robust standard errors). This argument accepts a covariance matrix, a function which returns a covariance matrix, or a string which identifies the function to be used to compute the covariance matrix.
A covariance matrix
A function which returns a covariance matrix (e.g., stats::vcov())
A string which indicates the kind of uncertainty estimates to return.
Heteroskedasticity-consistent: "HC", "HC0", "HC1", "HC2",
"HC3", "HC4", "HC4m", "HC5". See ?sandwich::vcovHC
Cluster-robust: "CR", "CR0", "CR1", "CR1p", "CR1S",
"CR2", "CR3". See ?clubSandwich::vcovCR
Bootstrap: "BS", "xy", "residual", "wild", "mammen",
"fractional", "jackknife", "norm", "webb". See
?sandwich::vcovBS
Other sandwich package functions: "HAC", "PC", "CL", "OPG",
"PL".
List of arguments to be passed to the function identified by
the vcov argument. This function is typically supplied by the
sandwich or clubSandwich packages. Please refer to their
documentation (e.g., ?sandwich::vcovHAC) to see the list of available
arguments. If no estimation type (argument type) is given, the default
type for "HC" equals the default from the sandwich package; for type
"CR", the default is set to "CR3".
Toggle warnings and messages.
Logical, if TRUE, factors are converted to numerical
values to calculate the standard error, with the lowest level being the
value 1 (unless the factor has numeric levels, which are converted
to the corresponding numeric value). By default, NA is returned for
factors or character vectors.
A data frame with at least two columns: the parameter names and the standard errors. Depending on the model, may also include columns for model components etc.
For Bayesian models (from rstanarm or brms), the standard error is the SD of the posterior samples.
model <- lm(Petal.Length ~ Sepal.Length * Species, data = iris)
standard_error(model)
#> Parameter SE
#> 1 (Intercept) 0.5310388
#> 2 Sepal.Length 0.1058237
#> 3 Speciesversicolor 0.6836543
#> 4 Speciesvirginica 0.6578142
#> 5 Sepal.Length:Speciesversicolor 0.1281447
#> 6 Sepal.Length:Speciesvirginica 0.1209952
# robust standard errors
standard_error(model, vcov = "HC3")
#> Parameter SE
#> 1 (Intercept) 0.42486667
#> 2 Sepal.Length 0.08504442
#> 3 Speciesversicolor 0.67252996
#> 4 Speciesvirginica 0.58942889
#> 5 Sepal.Length:Speciesversicolor 0.12045791
#> 6 Sepal.Length:Speciesvirginica 0.10558799
# cluster-robust standard errors
standard_error(model,
vcov = "vcovCL",
vcov_args = list(cluster = iris$Species)
)
#> Parameter SE
#> 1 (Intercept) 1.842490e-15
#> 2 Sepal.Length 3.678147e-16
#> 3 Speciesversicolor 1.843367e-15
#> 4 Speciesvirginica 2.279195e-15
#> 5 Sepal.Length:Speciesversicolor 3.679071e-16
#> 6 Sepal.Length:Speciesvirginica 4.186606e-16