| umxReduceACE {umx} | R Documentation |
Reduce an ACE model.
Description
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.
Usage
umxReduceACE(
model,
report = c("markdown", "inline", "html", "report"),
intervals = TRUE,
baseFileName = "tmp",
tryHard = c("yes", "no", "ordinal", "search"),
silent = FALSE,
digits = 2,
...
)
Arguments
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 |
Details
It is designed for testing univariate models. You can offer up either the ACE or ADE base model.
Suggestions for more sophisticated automation welcomed!
Value
Best fitting model
References
Wagenmakers, E.J., & Farrell, S. (2004). AIC model selection using Akaike weights. Psychonomic Bulletin and Review, 11, 192-196. doi:10.3758/BF03206482
See Also
Other Twin Modeling Functions:
power.ACE.test(),
umxACEcov(),
umxACEv(),
umxACE(),
umxCP(),
umxDiffMZ(),
umxDiscTwin(),
umxDoCp(),
umxDoC(),
umxGxE_window(),
umxGxEbiv(),
umxGxE(),
umxIP(),
umxMRDoC(),
umxReduceGxE(),
umxReduce(),
umxRotate.MxModelCP(),
umxSexLim(),
umxSimplex(),
umxSummarizeTwinData(),
umxSummaryACEv(),
umxSummaryACE(),
umxSummaryDoC(),
umxSummaryGxEbiv(),
umxSummarySexLim(),
umxSummarySimplex(),
umxTwinMaker(),
umx
Examples
## 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)