Make a direction of causation model based on umxPath statements
Makes a direction of causation model with umxPath() statements
umxDoCp(
var1Indicators,
var2Indicators,
mzData = NULL,
dzData = NULL,
sep = "_T",
causal = TRUE,
name = "DoC",
autoRun = getOption("umx_auto_run"),
intervals = FALSE,
tryHard = c("no", "yes", "ordinal", "search"),
optimizer = NULL
)var1Indicators |
The indicators of trait 1 |
var2Indicators |
The indicators of trait 2 |
mzData |
The MZ twin dataframe |
dzData |
The DZ twin dataframe |
sep |
(Default "_T") |
causal |
(Default TRUE) |
name |
= "DoC" |
autoRun |
Default: getOption("umx_auto_run")_ |
intervals |
Whether to run intervals (Default FALSE) |
tryHard |
Default "no" (valid = "yes", "ordinal", "search") |
optimizer |
Whether to set this for this run (Default no)) |
See also umxDoC()
[A direction of causation model with umxPath() statements.
Other Twin Modeling Functions:
power.ACE.test(),
umxACEcov(),
umxACEv(),
umxACE(),
umxCP(),
umxDoC(),
umxGxE_window(),
umxGxEbiv(),
umxGxE(),
umxIP(),
umxReduceACE(),
umxReduceGxE(),
umxReduce(),
umxRotate.MxModelCP(),
umxSexLim(),
umxSimplex(),
umxSummarizeTwinData(),
umxSummaryACEv(),
umxSummaryACE(),
umxSummaryDoC(),
umxSummaryGxEbiv(),
umxSummarySexLim(),
umxSummarySimplex(),
umxTwinMaker(),
umx
## Not run:
# ================
# = 1. Load Data =
# ================
data(docData)
var1 = paste0("varA", 1:3)
var2 = paste0("varB", 1:3)
tmp = umx_scale_wide_twin_data(varsToScale= c(var1, var2), sep= "_T", data= docData)
mzData = subset(docData, zygosity %in% c("MZFF", "MZMM"))
dzData = subset(docData, zygosity %in% c("DZFF", "DZMM"))
m1 = umxDoCp(var1, var2, mzData= mzData, dzData= dzData, sep = "_T", causal= TRUE)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.