Reviewers have requested I give confidence intervals on estimates from a common pathway model (I am using the umx::umxCP
function to build my common pathway model).
When I try and use Hunter's nice mxSE(top.es_std[1,1], model = cp3)
function on to request the SE on the specific-e for variable 1), I get the following error:
Model does not have a reasonable Hessian or standard errors.
Model has at least one mxConstraint. This prevented standard error computation.
Try mxCI()
Is there any work-around for this (to use mxSE
with a constraint in the model)?
Computing profile-based CIs will take a considerable time…
Can the CP model be implemented without constraints? the constraint used is
mxConstraint(diagL == nFac_Unit , name = "fix_CP_variances_to_1"),
Many thanks!
PS: Why do constraints invalidate SEs?