umx (version 4.20.0)

umxReduceACE: 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,
  ...
)

Value

Best fitting model

Arguments

model

an ACE or ADE mxModel() to reduce

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!

References

• Wagenmakers, E.J., & Farrell, S. (2004). AIC model selection using Akaike weights. Psychonomic Bulletin and Review, 11, 192-196. tools:::Rd_expr_doi("10.3758/BF03206482")

See Also

umxReduceGxE(), umxReduce()

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

if (FALSE) {
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)

}