When you have a multilevel model with lots of factors and interactions the size of the correlation of fixed effects matrix can become quite big and unclear.
I can us
Using the S4 method listing function we can return the function which is dispatched when print
is called on an object of class "mer"
:
selectMethod( print , "mer" )
Looking at the source code that is returned we can find the lines applicable to you:
if (correlation) {
corF <- so@vcov@factors$correlation
so
is defined as the summary of your object, so in your case you should just need to extract:
so <- summary(mod)
so@vcov@factors$correlation
How about using the built-in
cov2cor(vcov(mod))
?
I don't know direct method. But this is workaround.
diag(diag(1/sqrt(vcov(mod)))) %*% vcov(mod) %*% diag(diag(1/sqrt(vcov(mod))))