umxDiagnose | R Documentation |
The goal of this function WILL BE (not currently functional) to diagnose problems in a model and return suggestions to the user. It is a work in progress, and of no use as yet.
umxDiagnose(model, tryHard = FALSE, diagonalizeExpCov = FALSE)
model |
an |
tryHard |
whether I should try and fix it? (defaults to FALSE) |
diagonalizeExpCov |
Whether to diagonalize the ExpCov |
Best diagnostics are:
Observed data variances and means
Expected variances and means
Difference of these?
Try
* diagonalizeExpCov diagonal
* umx_is_ordered()
Tricky, but reporting variances and standardized thresholds is ideal. Guidance is to start with unit variances and thresholds within +/- 2 SD of the mean. Like %p option in Classic Mx.
helpful messages and perhaps a modified model
Other Teaching and Testing functions:
tmx_show.MxModel()
,
umxPower()
## Not run:
require(umx)
data(demoOneFactor)
manifests = names(demoOneFactor)
m1 = umxRAM("OneFactor", data = demoOneFactor, type= "cov",
umxPath("G", to = manifests),
umxPath(var = manifests),
umxPath(var = "G", fixedAt = 1)
)
m1 = mxRun(m1)
umxSummary(m1, std = TRUE)
umxDiagnose(m1)
## End(Not run)
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