Given a umx model (currently umxACE and umxGxE are supported - ask for more!)
umxReduce will conduct a formalised reduction process. It will also report
Akaike weights are also reported showing relative support across models.
Specialized functions are called for different type of input:
GxE model reduction For umxGxE() models umxReduceGxE() is called.
ACE model reduction For umxACE() models,umxReduceACE() is called.
umxReduce reports the results in a table. Set the format of the table with
umx_set_table_format(), or set report= "html" to open a
table for pasting into a word processor.
umxReduce is a work in progress, with more automatic reductions coming as demand emerges.
I am thinking for RAM models to drop NS paths, and report that test.
umxReduce(
model,
report = c("markdown", "inline", "html"),
baseFileName = "tmp",
...
)The mxModel() which will be reduced.
How to report the results. "html" = open in browser
(optional) custom filename for html output (defaults to "tmp")
Other parameters to control model summary
Wagenmakers, E.J., & Farrell, S. (2004). AIC model selection using Akaike weights. Psychonomic Bulletin and Review, 11, 192-196. doi:
umxReduceGxE(), umxReduceACE()
Other Reporting Functions:
loadings.MxModel(),
umxAPA(),
umxFactorScores(),
umxGetParameters(),
umxParameters(),
umx_aggregate(),
umx_names(),
umx_time(),
umx
Other Twin Reporting Functions:
umxPlotCP(),
umxPlotDoC(),
umxReduceACE(),
umxReduceGxE(),
umxSummarizeTwinData(),
umxSummaryACEcov(),
umxSummaryACEv(),
umxSummaryACE(),
umxSummaryCP(),
umxSummaryDoC(),
umxSummaryGxEbiv(),
umxSummaryGxE(),
umxSummaryIP(),
umxSummarySexLim(),
umxSummarySimplex(),
umx