| umxDiffMZ {umx} | R Documentation |
MZ differences method for testing evidence for causality.
Description
umxDiffMZ implements the simple twin1-twin2 based correlation method, e.g. De Moor (2008), in which MZ differences
on a variable x asserted to be causal of an outcome variable y are tested for association with differences on y.
The logic of the design is shown below:
Usage
umxDiffMZ(
x,
y,
data,
sep = "_T",
mzZygs = c("MZFF", "MZMM"),
zyg = "zygosity",
labxy = c(-1.2, 1.8),
xylim = c(NA, NA),
digits = 2
)
Arguments
x |
Presumed causal variable, e.g. "effort" |
y |
Presumed caused outcome, e.g. "score" |
data |
Dataframe containing the twin data. |
sep |
The separator "_T" used to make twin var names from x and y. |
mzZygs |
The MZ zygosity codes c("MZFF", "MZMM") |
zyg |
The column containing "zygosity" data |
labxy |
Where to locate the R2 label (default = c(x=-2,y=3)) |
xylim |
= clip x any axes to range, e.g c(-3,-3) |
digits |
Rounding for beta (def2) |
Details
Example output is shown below, with the fitted line and fit inscribed. The plot is just a ggplot graph that is returned and can be edited and formatted.
For a more sophisticated linear mixed model approach, see umxDiscTwin().
Value
Graph for decorating
References
De Moor, M. H., Boomsma, D. I., Stubbe, J. H., Willemsen, G., & de Geus, E. J. (2008). Testing causality in the association between regular exercise and symptoms of anxiety and depression. Archives of General Psychiatry, 65(8), 897-905. doi:10.1001/archpsyc.65.8.897.
See Also
Other Twin Modeling Functions:
power.ACE.test(),
umxACEcov(),
umxACEv(),
umxACE(),
umxCP(),
umxDiscTwin(),
umxDoCp(),
umxDoC(),
umxGxE_window(),
umxGxEbiv(),
umxGxE(),
umxIP(),
umxMRDoC(),
umxReduceACE(),
umxReduceGxE(),
umxReduce(),
umxRotate.MxModelCP(),
umxSexLim(),
umxSimplex(),
umxSummarizeTwinData(),
umxSummaryACEv(),
umxSummaryACE(),
umxSummaryDoC(),
umxSummaryGxEbiv(),
umxSummarySexLim(),
umxSummarySimplex(),
umxTwinMaker(),
umx
Examples
data(twinData)
umxDiffMZ(x="ht", y="wt", labxy = c(-.5, 3), data = twinData, sep = "")
umxDiffMZ(x="ht", y="wt", xylim = c( -2, 2), data = twinData, sep = "")