# NOT RUN {
require(umx)
data(demoOneFactor)
latents = c("G")
manifests = names(demoOneFactor)
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 = 1.0),
mxData(cov(demoOneFactor), type = "cov", numObs = 500)
)
m1 = umxRun(m1) # just run: will create saturated model if needed
m1 = umxRun(m1, setValues = TRUE, setLabels = TRUE) # set start values and label all parameters
umxSummary(m1, show = "std")
m1 = mxModel(m1, mxCI("G_to_x1")) # add one CI
m1 = mxRun(m1, intervals = TRUE)
residuals(m1, run = TRUE) # get CIs on all free parameters
confint(m1) # OpenMx's SE-based CIs
umxConfint(m1, run = TRUE) # get likelihood-based CIs on all free parameters
m1 = umxRun(m1, n = 10) # re-run up to 10 times if not green on first run
# }
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