umx (version 4.0.0)

umxSummaryDoC: Shows a compact, publication-style, summary of a umx 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. the report parameter allows drawing the tables to a web browser where they may readily be copied into non-markdown programs like Word.

Usage

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

Arguments

model

a fitted umxDoC() model to summarize.

digits

round to how many digits (default = 2).

comparison

Run mxCompare on a comparison model (default 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

Print tables to the console (as 'markdown'), or open in browser ('html')

file

The name of the dot file to write: "name" = use the name of the model. Defaults to NA = do not create plot output.

returnStd

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

zero.print

How to show zeros (".")

...

Other parameters to control model summary.

Value

• optional mxModel()

Details

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

See Also

• umxDoC(), plot.MxModelDoC(), umxModify(), umxCP(), plot(), umxSummary() work for IP, CP, GxE, SAT, and ACE models.

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

Examples

# NOT RUN {
# ================
# = 1. Load Data =
# ================
umx_set_auto_plot(FALSE) # turn off autoplotting for CRAN
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")
A2B = umxModify(DoC, "a2b", free = TRUE, name = "A2B", comp=TRUE)
B2A = umxModify(DoC, "b2a", free = TRUE, name = "B2A", comp=TRUE)
umxCompare(B2A, A2B)

# }