Sandwich: Sandwich estimators for standard errors

In NormData: Derivation of Regression-Based Normative Data

Sandwich estimators for standard errors

Description

The Sandwich() function can be used to obtain heteroscedasticity-consistent standard errors of the regression parameters of a fitted Stage 1 model. These are used to account for heteroscedasticity.

Usage

Sandwich(Stage.1.Model, Type="HC0")

Arguments

Stage.1.Model	The fitted stage 1 model for which heteroscedasticity-consistent standard errors (sandwich estimators) for the standard errors of the regression parameters has to be provided.
Type	The type of the heteroscedasticity-consistent estimator that is used. By default, White's (White, 1980) estimator is used (i.e., Type="HC0") but other estimators are available. For details, see the vcovHC function of the sandwich package.

Value

Sandwich	The fitted Stage 1 model with sandwich estimators.
Alpha	The significance level that is used for inference. Default Alpha=0.05.

Author(s)

Wim Van der Elst

References

Van der Elst, W. (2024). Regression-based normative data for psychological assessment: A hands-on approach using R. Springer Nature.

White, H. (1980). A heteroscedasticity-consistent covariance matrix and a direct test for heteroscedasticity. Econometrica, 48, 817-838.

See Also

Stage.1

Examples

data(GCSE)
Model.1.GCSE <- Stage.1(Dataset = GCSE, Model = Science.Exam~Gender)
Sandwich(Stage.1.Model = Model.1.GCSE)

NormData documentation built on May 29, 2024, 6:23 a.m.