umx (version 4.0.0)

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"),
  baseFileName = "tmp",
  intervals = TRUE,
  ...
)

Arguments

model

an ACE or ADE mxModel() to reduce

report

How to report the results. "html" = open in browser

baseFileName

(optional) custom filename for html output (defaults to "tmp")

intervals

Recompute CIs (if any included) on the best model (default = TRUE)

...

Other parameters to control model summary

Value

Best fitting model

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. doi:

See Also

umxReduceGxE(), umxReduce()

Other Twin Reporting Functions: umxPlotCP(), umxPlotDoC(), umxReduceGxE(), umxReduce(), umxSummarizeTwinData(), umxSummaryACEcov(), umxSummaryACEv(), umxSummaryACE(), umxSummaryCP(), umxSummaryDoC(), umxSummaryGxEbiv(), umxSummaryGxE(), umxSummaryIP(), umxSummarySexLim(), umxSummarySimplex(), 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 = "")
m2 = umxReduce(m1)
umxSummary(m2)
m1 = umxACE(selDVs = "bmi", dzData = dzData, mzData = mzData, sep = "", dzCr = .25)
m2 = umxReduce(m1)

# }