Learn R Programming

umx (version 4.0.0)

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

See Also

Other Modify or Compare Models: umxEquate(), umxFixAll(), umxModify(), umxSetParameters(), umxUnexplainedCausalNexus(), umx

Examples

Run this code
# 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)
)
# umxMI(m1, full=FALSE)
# }

Run the code above in your browser using DataLab