umx (version 4.0.0)

umxExpCov: Get the expected vcov matrix

Description

Extract the expected covariance matrix from an mxModel()

Usage

umxExpCov(object, latents = FALSE, manifests = TRUE, digits = NULL, ...)

Arguments

object

an mxModel() to get the covariance matrix from

latents

Whether to select the latent variables (defaults to TRUE)

manifests

Whether to select the manifest variables (defaults to TRUE)

digits

precision of reporting. NULL (Default) = no rounding.

...

extra parameters (to match vcov())

Value

• expected covariance matrix

References

• https://openmx.ssri.psu.edu/thread/2598 Original written by https://openmx.ssri.psu.edu/users/bwiernik

See Also

• umxRun(), umxCI_boot()

Other Reporting functions: RMSEA.MxModel(), RMSEA.summary.mxmodel(), RMSEA(), extractAIC.MxModel(), loadings(), residuals.MxModel(), umxCI_boot(), umxCI(), umxCompare(), umxConfint(), umxExpMeans(), umxFitIndices(), umxPlotACEv(), umxRotate(), umxSummary.MxModel()

Examples

# NOT RUN {
require(umx)
data(demoOneFactor)
manifests = names(demoOneFactor)
m1 = umxRAM("One Factor", data = demoOneFactor, type = "cov",
	umxPath("G", to = manifests),
	umxPath(var = manifests),
	umxPath(var = "G", fixedAt = 1)
)#'
vcov(m1) # supplied by OpenMx
umxExpCov(m1, digits = 3)
# }

Run the code above in your browser using DataCamp Workspace