umx (version 4.9.0)

umxRun: umxRun: Run an mxModel

Description

umxRun is a version of mxRun() which can run also set start values, labels, and run multiple times It can also calculate the saturated and independence likelihoods necessary for most fit indices. Note this is not needed for umxRAM models or twin models - it is just a convenience to get base OpenMx models to run.

Usage

umxRun(
  model,
  n = 1,
  calc_SE = TRUE,
  calc_sat = TRUE,
  setValues = FALSE,
  setLabels = FALSE,
  intervals = FALSE,
  comparison = NULL
)

Arguments

model

The mxModel() you wish to run.

n

The maximum number of times you want to run the model trying to get a code green run (defaults to 1)

calc_SE

Whether to calculate standard errors (ignored when n = 1) for the summary (if you use mxCI() or umxCI(), you can turn this off)

calc_sat

Whether to calculate the saturated and independence models (for raw mxData() mxModel()s) (defaults to TRUE - why would you want anything else?)

setValues

Whether to set the starting values of free parameters (default = FALSE)

setLabels

Whether to set the labels (default = FALSE)

intervals

Whether to run mxCI confidence intervals (default = FALSE) intervals = FALSE

comparison

Whether to run umxCompare() after umxRun

Value

• mxModel()

References

• https://github.com/tbates/umx

See Also

Other Advanced Model Building Functions: umxAlgebra(), umxFixAll(), umxJiggle(), umxThresholdMatrix(), umxUnexplainedCausalNexus(), umx, xmuLabel(), xmuValues()

Examples

# 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
# }
# NOT RUN {
m1 = umxRun(m1, setValues = TRUE, setLabels = TRUE) # set start values and label all parameters
umxSummary(m1, std = TRUE)
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
# }
# NOT RUN {
# }