standard_error: Standard Errors

In parameters: Processing of Model Parameters

Standard Errors

Description

standard_error() attempts to return standard errors of model parameters.

Usage

standard_error(model, ...)

## Default S3 method:
standard_error(
  model,
  component = "all",
  vcov = NULL,
  vcov_args = NULL,
  verbose = TRUE,
  ...
)

## S3 method for class 'factor'
standard_error(model, force = FALSE, verbose = TRUE, ...)

## S3 method for class 'glmmTMB'
standard_error(
  model,
  effects = "fixed",
  component = "all",
  verbose = TRUE,
  ...
)

## S3 method for class 'merMod'
standard_error(
  model,
  effects = "fixed",
  method = NULL,
  vcov = NULL,
  vcov_args = NULL,
  ...
)

Arguments

model	A model.
...	Arguments passed to or from other methods.
component	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.
vcov	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: "vcovHC", "HC", "HC0", "HC1", "HC2", "HC3", "HC4", "HC4m", "HC5". See ?sandwich::vcovHC. Cluster-robust: "vcovCR", "CR0", "CR1", "CR1p", "CR1S", "CR2", "CR3". See ?clubSandwich::vcovCR. Bootstrap: "vcovBS", "xy", "residual", "wild", "mammen", "webb". See ?sandwich::vcovBS. Other sandwich package functions: "vcovHAC", "vcovPC", "vcovCL", "vcovPL".
vcov_args	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.
verbose	Toggle warnings and messages.
force	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.
effects	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.
method	Method for computing degrees of freedom for confidence intervals (CI) and the related p-values. Allowed are following options (which vary depending on the model class): "residual", "normal", "likelihood", "satterthwaite", "kenward", "wald", "profile", "boot", "uniroot", "ml1", "betwithin", "hdi", "quantile", "ci", "eti", "si", "bci", or "bcai". See section Confidence intervals and approximation of degrees of freedom in model_parameters() for further details.

Value

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.

Note

For Bayesian models (from rstanarm or brms), the standard error is the SD of the posterior samples.

Examples

model <- lm(Petal.Length ~ Sepal.Length * Species, data = iris)
standard_error(model)

if (require("sandwich") && require("clubSandwich")) {
  standard_error(model, vcov = "HC3")

  standard_error(model,
    vcov = "vcovCL",
    vcov_args = list(cluster = iris$Species)
  )
}

parameters documentation built on Nov. 2, 2023, 6:13 p.m.