View source: R/build_run_modify.R
umxRotate.MxModelCP | R Documentation |
Rotate a CP solution.
Should work with rotations provided in library("GPArotation")
and library("psych")
, e.g
Orthogonal: "varimax", "quartimax", "bentlerT", "equamax", "varimin", "geominT" and "bifactor"
Oblique: "Promax", "promax", "oblimin", "simplimax", "bentlerQ", "geominQ", "biquartimin" and "cluster"
## S3 method for class 'MxModelCP'
umxRotate(
model,
rotation = c("varimax", "promax"),
tryHard = "yes",
freeLoadingsAfter = TRUE,
verbose = TRUE
)
model |
a |
rotation |
name of the rotation. |
tryHard |
Default ("yes") is to tryHard. |
freeLoadingsAfter |
return the model with factor loadings free (default) or fixed in the new locations. |
verbose |
print detail about the rotation |
This works by taking the common-pathways loadings matrix from a solved umxCP()
model, rotating these, placing
them back into the loadings matrix, re-estimating the model with the parameters fixed at this rotation, then return the new model.
Rotated solution.
umxCP()
Other Twin Modeling Functions:
power.ACE.test()
,
umxACEcov()
,
umxACEv()
,
umxACE()
,
umxCP()
,
umxDiffMZ()
,
umxDiscTwin()
,
umxDoCp()
,
umxDoC()
,
umxGxE_window()
,
umxGxEbiv()
,
umxGxE()
,
umxIP()
,
umxMRDoC()
,
umxReduceACE()
,
umxReduceGxE()
,
umxReduce()
,
umxSexLim()
,
umxSimplex()
,
umxSummarizeTwinData()
,
umxSummaryACEv()
,
umxSummaryACE()
,
umxSummaryDoC()
,
umxSummaryGxEbiv()
,
umxSummarySexLim()
,
umxSummarySimplex()
,
umxTwinMaker()
,
umx
## Not run:
# Rotate a CP solution(param)
# Common pathway model rotation
library(umx)
# Fit 3 factor CPM
data(GFF)
selDVs = c("gff", "fc", "qol", "hap", "sat", "AD")
m1 = umxCP(selDVs = selDVs, nFac = 2, data = data, tryHard = "yes")
m2 = umxRotate(m1, rotation = "varimax", tryHard = "yes")
## End(Not run)
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