umx (version 1.9.1)

umxMI: Report modifications which would improve fit.

Description

This function uses the mechanical modification-indices approach to detect single paths which, if added or dropped, would improve fit.

Usage

umxMI(model = NA, matrices = NA, full = TRUE, numInd = NA,
  typeToShow = "both", decreasing = TRUE)

Arguments

model

An mxModel for which to report modification indices

matrices

which matrices to test. The default (NA) will test A & S for RAM models

full

Change in fit allowing all parameters to move. If FALSE only the parameter under test can move.

numInd

How many modifications to report. Use -1 for all. Default (NA) will report all over 6.63 (p = .01)

typeToShow

Whether to shown additions or deletions (default = "both")

decreasing

How to sort (default = TRUE, decreasing)

Details

Notes: 1. Runs much faster with full = FALSE (but this does not allow the model to re-fit around the newly- freed parameter). 2. Compared to mxMI, this function returns top changes, and also suppresses the run message. 3. Finally, of course: see the requirements for (legitimate) post-hoc modeling in mxMI You are almost certainly doing better science when testing competing models rather than modifying a model to fit.

References

- http://www.github.com/tbates/umx

See Also

- mxMI

Other Modify or Compare Models: umxAdd1, umxDrop1, umxEquate, umxFixAll, umxSetParameters, umxUnexplainedCausalNexus, umx

Examples

# NOT RUN {
require(umx)
data(demoOneFactor)
latents  = c("G")
manifests = names(demoOneFactor)[1:3]
df = mxData(cov(demoOneFactor[,manifests]), type = "cov", numObs = 500)
m1 <- umxRAM("One Factor", data = df,
	umxPath(latents, to = manifests),
	umxPath(var = manifests),
	umxPath(var = latents, fixedAt = 1)
)
umxMI(m1, full=FALSE)
# }