Joshua Wiley <jwiley.psych at ...> writes:
Hi,
I am trying to use a multivariate mixed effects linear model to
examine mediation. ?This works fine. ?The final step is to compute the
indirect effect and its standard error. ?The indirect effect is easy
(product of coefficients plus their covariance). ?For the standard
error, I need the gradient (D) and the hessian (H):
the variance is then:
D'\Sigma(\theta)D + \frac{1}{2}Tr{(\mathbf{H}\boldsymbol{\Sigma}(\theta))^{2}}
This is all given in the Appendix of
http://www.unc.edu/~dbauer/manuscripts/bauer-preacher-gil-PM-2006.pdf
Is there a way to get this out of a mer class object? ?Looking at
class?mer, the appropriate bits of vcov give me $\Sigma(\theta)$. ?@V
seems like it would give me the gradient but is null for a basic lmer
model.
?If you're willing to try out the development version (i.e., lme4
from r-forge), I think you can do this as follows:
fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy)
fm1Fun <- update(fm1,devFunOnly=TRUE)
library(numDeriv)
fm1_thpar <- getME(fm1,"theta")
h <- hessian(fm1Fun,fm1_thpar)
?and similarly for the gradient.
?Let me know how it goes.
?Ben Bolker