mxSE {OpenMx} | R Documentation |
This function allows you to obtain standard errors for arbitrary expressions, named entities, and algebras.
mxSE(x, model, details = FALSE, ...)
x |
the parameter to get SEs on (reference or expression) |
model |
the |
details |
logical. Whether to provide further details, e.g. the full sampling covariance matrix of x. |
... |
further named arguments passed to |
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.
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.
- https://en.wikipedia.org/wiki/Standard_error
- mxCI
library(OpenMx) data(demoOneFactor) # =============================== # = 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), 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('A', model = m1) mxSE((A + A) %*% S, model = m1) mxSE(S, model = m1) mxSE(A[1,2], model = m1) mxSE(A[1,6]^2, model = m1) mxSE(A[,6]%^%2, model = m1, details = TRUE)