mxSE {OpenMx}R Documentation

Compute standard errors in OpenMx


This function allows you to obtain standard errors for arbitrary expressions, named entities, and algebras.


mxSE(x, model, details = FALSE, cov, ...)



the parameter to get SEs on (reference or expression)


the mxModel to use.


logical. Whether to provide further details, e.g. the full sampling covariance matrix of x.


optional matrix of covariances among the free parameters. If missing, the inverse Hessian from the fitted model is used.


further named arguments passed to mxEval


x can be the name of an algebra, a bracket address, named entity or arbitrary expression. It is a frontend-only file that works much like mxEval. When the details argument is TRUE, the full sampling covariance matrix of x is also returned as part of a list. The square root of the diagonals of this sampling covariance matrix are the standard errors.

When supplying the cov argument, take care that the free parameter covariance matrix is given, not the information matrix. These two are inverses of one another.


SE value(s) returned as a matrix when details is FALSE. When details is TRUE, a list of the SE value(s) and the full sampling covariance matrix.



See Also

- mxCI


# ===============================
# = Make and run a 1-factor CFA =
# ===============================

latents  = c("G") # the latent factor
manifests = names(demoOneFactor) # manifest variables to be modeled
# ===========================
# = Make and run the model! =
# ===========================
m1 <- mxModel("One Factor", type = "RAM", 
	manifestVars = manifests, latentVars = latents, 
	mxPath(from = latents, to = manifests, labels=paste0('lambda', 1:5)),
	mxPath(from = manifests, arrows = 2),
	mxPath(from = latents, arrows = 2, free = FALSE, values = 1),
	mxData(cov(demoOneFactor), type = "cov", numObs = 500)
m1 = mxRun(m1)
mxSE(lambda5, model = m1)
mxSE(lambda1^2, model = m1)

[Package OpenMx version 2.8.3 Index]