bda (version 1.2.7-31)

mediation.test: The Sobel mediation test

Description

To compute statistics and p-values for the Sobel test. Results for three versions of "Sobel test" are provided: Sobel test, Aroian test and Goodman test.

Usage

mediation.test(mv,iv,dv)

Arguments

mv

The mediator variable.

iv

The independent variable.

dv

The dependent variable.

Value

• Missing values are not allowed.

Details

To test whether a mediator carries the influence on an IV to a DV.

References

MacKinnon, D. P., & Dwyer, J. H. (1993). Estimating mediated effects in prevention studies. Evaluation Review, 17, 144-158.

MacKinnon, D. P., Warsi, G., & Dwyer, J. H. (1995). A simulation study of mediated effect measures. Multivariate Behavioral Research, 30, 41-62.

Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods,Instruments, & Computers, 36, 717-731. Preacher, K. J., & Hayes, A. F. (2008). asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, Instruments, & Computers, 40, 879-891.

Wang, B. and Wertelecki, W. (2012) Density Estimation for Data With Rounding Errors. Computational Statistics and Data Analysis, (in press), doi: 10.1016/j.csda.2012.02.016.

See Also

gof,perm.test.

Examples

mv = rnorm(100)
iv = rnorm(100)
dv = rnorm(100)
mediation.test(mv,iv,dv)