View source: R/umx_build_umxACEv.R
| umxSummaryACEv | R Documentation |
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.
umxSummaryACEv(
model,
digits = 2,
comparison = NULL,
std = TRUE,
showRg = FALSE,
CIs = TRUE,
report = c("markdown", "html"),
file = getOption("umx_auto_plot"),
returnStd = FALSE,
extended = FALSE,
zero.print = ".",
show = c("std", "raw"),
...
)
model |
an |
digits |
round to how many digits (default = 2) |
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 |
file |
The name of the dot file to write: "name" = use the name of the model. Defaults to getOption("umx_auto_plot"), which is likely "name". |
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 |
See documentation for other umx models here: umxSummary().
optional OpenMx::mxModel()
umxACEv()
Other Twin Modeling Functions:
power.ACE.test(),
umx,
umxACE(),
umxACEcov(),
umxACEv(),
umxCP(),
umxDiffMZ(),
umxDiscTwin(),
umxDoC(),
umxDoCp(),
umxGxE(),
umxGxE_window(),
umxGxEbiv(),
umxIP(),
umxMRDoC(),
umxReduce(),
umxReduceACE(),
umxReduceGxE(),
umxRotate.MxModelCP(),
umxSexLim(),
umxSimplex(),
umxSummarizeTwinData(),
umxSummaryACE(),
umxSummaryDoC(),
umxSummaryGxEbiv(),
umxSummarySexLim(),
umxSummarySimplex(),
umxTwinMaker()
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)
## End(Not run)
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