bda (version 14.3.19)

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

a table showing the values of the test statistics (z-values) and the corresponding p-values for three tests, namely the Sobel test, Aroian test and Goodman test, respectively.

Details

To test whether a mediator carries the influence on an IV to a DV. Missing values will be automatically excluded with a warning.

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.

Examples

# NOT RUN {
mv = rnorm(100)
iv = rnorm(100)
dv = rnorm(100)
mediation.test(mv,iv,dv)
# }