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umx (version 4.0.0)

umxSummaryACEv: Shows a compact, publication-style, summary of a variance-based Cholesky ACE model.

Description

Summarize a fitted Cholesky model returned by umxACEv(). Can control digits, report comparison model fits, optionally show the Rg (genetic and environmental correlations), and show confidence intervals. the report parameter allows drawing the tables to a web browser where they may readily be copied into non-markdown programs like Word.

Usage

umxSummaryACEv(
  model,
  digits = 2,
  file = getOption("umx_auto_plot"),
  comparison = NULL,
  std = TRUE,
  showRg = FALSE,
  CIs = TRUE,
  report = c("markdown", "html"),
  returnStd = FALSE,
  extended = FALSE,
  zero.print = ".",
  show = c("std", "raw"),
  ...
)

Arguments

model

an mxModel() to summarize

digits

round to how many digits (default = 2)

file

The name of the dot file to write: "name" = use the name of the model. Defaults to NA = no plot.

comparison

you can run mxCompare on a comparison model (NULL)

std

Whether to standardize the output (default = TRUE)

showRg

= whether to show the genetic correlations (FALSE)

CIs

Whether to show Confidence intervals if they exist (TRUE)

report

If "html", then open an html table of the results

returnStd

Whether to return the standardized form of the model (default = FALSE)

extended

how much to report (FALSE)

zero.print

How to show zeros (".")

show

Here to support being called from generic xmu_safe_run_summary. User should ignore: can be c("std", "raw")

...

Other parameters to control model summary

Value

Details

See documentation for other umx models here: umxSummary().

References

See Also

Other Twin Reporting Functions: umxPlotCP(), umxPlotDoC(), umxReduceACE(), umxReduceGxE(), umxReduce(), umxSummarizeTwinData(), umxSummaryACEcov(), umxSummaryACE(), umxSummaryCP(), umxSummaryDoC(), umxSummaryGxEbiv(), umxSummaryGxE(), umxSummaryIP(), umxSummarySexLim(), umxSummarySimplex(), umx

Examples

Run this code
# NOT RUN {
require(umx)
data(twinData)
mzData = subset(twinData, zygosity == "MZFF")
dzData = subset(twinData, zygosity == "DZFF")
m1 = umxACEv(selDVs = "bmi", sep = "", dzData = dzData, mzData = mzData)
umxSummary(m1, std = FALSE)
# }
# NOT RUN {
umxSummary(m1, file = NA);
umxSummary(m1, file = "name", std = TRUE)
stdFit = umxSummary(m1, returnStd = TRUE)
# }

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