View source: R/indirectEffect.R
indirectEffect | R Documentation |
It estimates the standardized or unstandardized indirect and direct effects and their asymptotic sampling covariance matrix.
indirectEffect(x, n, standardized = TRUE, direct.effect = TRUE, run = TRUE)
x |
A 3x3 correlation/covariance matrix or a list of correlation/covariance matrices. Variables are arranged as the dependent variable (y), mediator (m) and independent variable (x) |
n |
Sample size or a vector of sample sizes |
standardized |
Logical. Whether the indirect effect is standardized. |
direct.effect |
Logical. Whether the direct effect is
estimated. If it is |
run |
Logical. If |
Cheung (2009) estimated the standardized indirect effect and
its standard error with non-linear constraints. Since OpenMx
does not generate standard errors when there
are non-linear constraints, Kwan and Chan's (2011) approach is used in
this function. Delta method is used to calculate the asymptotic covariance matrix.
A vector (or a matrix if the input is a list of matrices) of (standardized) indirect effect, standardized direct effect, and their asymptotic sampling covariance matrices
Mike W.-L. Cheung <mikewlcheung@nus.edu.sg>
Cheung, M. W.-L. (2009). Comparison of methods for constructing confidence intervals of standardized indirect effects. Behavior Research Methods, 41, 425-438.
Kwan, J., & Chan, W. (2011). Comparing standardized coefficients in structural equation modeling: a model reparameterization approach. Behavior Research Methods, 43, 730-745.
## A correlation matrix as input
x <- matrix(c(1, 0.4, 0.2, 0.4, 1, 0.3, 0.2, 0.3, 1), ncol=3)
dimnames(x) <- list( c("y", "m", "x"), c("y", "m", "x") )
indirectEffect(x, n=300)
## A list of correlation matrices
indirectEffect( list(x, x), n=c(300,500), standardized=FALSE )
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