umxPlotDoC: Plot a Direction of Causation Model.

In umx: Structural Equation Modeling and Twin Modeling in R

Plot a Direction of Causation Model.

Description

Summarize a fitted model returned by umxDoC(). Can control digits, report comparison model fits, optionally show the Rg (genetic and environmental correlations), and show confidence intervals. note: std is not implemented as yet. See documentation for other umx models here: umxSummary().

Usage

umxPlotDoC(
  x = NA,
  means = FALSE,
  std = FALSE,
  digits = 2,
  showFixed = TRUE,
  file = "name",
  format = c("current", "graphviz", "DiagrammeR"),
  SEstyle = FALSE,
  strip_zero = FALSE,
  ...
)

Arguments

x	a umxDoC() model to display graphically
means	Whether to show means paths (defaults to FALSE)
std	Whether to standardize the model (defaults to TRUE)
digits	How many decimals to include in path loadings (defaults to 2)
showFixed	Whether to graph paths that are fixed but != 0 (default = TRUE)
file	The name of the dot file to write: NA = none; "name" = use the name of the model
format	= c("current", "graphviz", "DiagrammeR")
SEstyle	report "b (se)" instead of "b [lower, upper]" when CIs are found (Default FALSE)
strip_zero	Whether to strip the leading "0" and decimal point from parameter estimates (default = TRUE)
...	Other parameters to control model summary.

Value

• Optionally return the dot code

References

• https://tbates.github.io

See Also

• umxDoC(), umxSummary.MxModelDoC(), umxModify(), umxDiscTwin(), umxDiffMZ(), umxMR()

Other Plotting functions: ggAddR(), plot.MxLISRELModel(), plot.MxModel(), plot.MxModelTwinMaker(), umx, umxPlot(), umxPlotACE(), umxPlotACEcov(), umxPlotACEv(), umxPlotCP(), umxPlotFun(), umxPlotGxE(), umxPlotGxEbiv(), umxPlotIP(), umxPlotPredict(), umxPlotSexLim(), umxPlotSimplex()

Examples

## Not run: 
# ================
# = 1. Load Data =
# ================
data(docData)
mzData = subset(docData, zygosity %in% c("MZFF", "MZMM"))
dzData = subset(docData, zygosity %in% c("DZFF", "DZMM"))

# =======================================
# = 2. Define manifests for var 1 and 2 =
# =======================================
var1 = paste0("varA", 1:3)
var2 = paste0("varB", 1:3)

# =======================================================
# = 2. Make the non-causal (Cholesky) and causal models =
# =======================================================
Chol= umxDoC(var1= var1, var2= var2, mzData= mzData, dzData= dzData, causal= FALSE)
DoC = umxDoC(var1= var1, var2= var2, mzData= mzData, dzData= dzData, causal= TRUE)

# ================================================
# = Make the directional models by modifying DoC =
# ================================================
a2b = umxModify(DoC, "a2b", free = TRUE, name = "A2B")
plot(a2b)


## End(Not run)

umx documentation built on Nov. 5, 2025, 5:26 p.m.