Reduce an ACE model.
This function can perform model reduction on umxACE()
models,
testing dropping A and C, as well as an ADE or ACE model, displaying the results
in a table, and returning the best model.
umxReduceACE( model, report = c("markdown", "inline", "html", "report"), intervals = TRUE, baseFileName = "tmp", tryHard = c("yes", "no", "ordinal", "search"), silent = FALSE, digits = 2, ... )
model |
an ACE or ADE |
report |
How to report the results. "html" = open in browser |
intervals |
Recompute CIs (if any included) on the best model (default = TRUE) |
baseFileName |
(optional) custom filename for html output (defaults to "tmp") |
tryHard |
(default = "yes") |
silent |
Don't print the ACE models (default = FALSE) |
digits |
rounding in printout (default = 2) |
... |
Other parameters to control model summary |
It is designed for testing univariate models. You can offer up either the ACE or ADE base model.
Suggestions for more sophisticated automation welcomed!
Best fitting model
Wagenmakers, E.J., & Farrell, S. (2004). AIC model selection using Akaike weights. Psychonomic Bulletin and Review, 11, 192-196. doi: 10.3758/BF03206482
Other Twin Modeling Functions:
power.ACE.test()
,
umxACEcov()
,
umxACEv()
,
umxACE()
,
umxCP()
,
umxDoCp()
,
umxDoC()
,
umxGxE_window()
,
umxGxEbiv()
,
umxGxE()
,
umxIP()
,
umxReduceGxE()
,
umxReduce()
,
umxRotate.MxModelCP()
,
umxSexLim()
,
umxSimplex()
,
umxSummarizeTwinData()
,
umxSummaryACEv()
,
umxSummaryACE()
,
umxSummaryDoC()
,
umxSummaryGxEbiv()
,
umxSummarySexLim()
,
umxSummarySimplex()
,
umxTwinMaker()
,
umx
## Not run: data(twinData) mzData = subset(twinData, zygosity == "MZFF") dzData = subset(twinData, zygosity == "DZFF") m1 = umxACE(selDVs = "bmi", dzData = dzData, mzData = mzData, sep = "") # =========================================================================== # = Table of parameters + fit comparisons, ready too copy to word processor = # =========================================================================== umxReduce(m1, silent=TRUE, digits=2, repo="h") # ========================================== # = Function captures the preferred model = # ========================================== m2 = umxReduce(m1) umxSummary(m2) # works for ADE input also m1 = umxACE(selDVs = "bmi", dzData = dzData, mzData = mzData, sep = "", dzCr = .25) ## End(Not run)
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