umx (version 1.7.5)

umxACEcov: umxACEcov: Build and run a Cholesky with covariates in the covariance

Description

Make a 2-group ACE Cholesky Twin model with covariates modeled (see Details below)

Usage

umxACEcov(name = "ACEcov", selDVs, selCovs, dzData, mzData, suffix = NULL,
  dzAr = 0.5, dzCr = 1, addStd = TRUE, addCI = TRUE, boundDiag = NULL,
  equateMeans = TRUE, bVector = FALSE, thresholds = c("deviationBased",
  "left_censored"), autoRun = getOption("umx_auto_run"))

Arguments

name

The name of the model (defaults to"ACE")

selDVs

The variables to include from the data (do not include suffixes)

selCovs

The covariates to include from the data (do not include suffixes)

dzData

The DZ dataframe

mzData

The MZ dataframe

suffix

suffix for twin 1 and twin 2, often "_T" Used to expand selDVs into full column names, i,e "dep" --> c("dep_T1", "dep_T2")

dzAr

The DZ genetic correlation (defaults to .5, vary to examine assortative mating)

dzCr

The DZ "C" correlation (defaults to 1: set to .25 to make an ADE model)

addStd

Whether to add the algebras to compute a std model (defaults to TRUE)

addCI

Whether to add intervals to compute CIs (defaults to TRUE)

boundDiag

= Whether to bound the diagonal of the a, c, and e matrices

equateMeans

Whether to equate the means across twins (defaults to TRUE)

bVector

Whether to compute row-wise likelihoods (defaults to FALSE)

thresholds

How to implement ordinal thresholds: c("deviationBased", "left_censored")

autoRun

Whether to run the model and return it, or just return it

Value

- mxModel of subclass mxModel.ACEcov

Details

umxACEcov supplements the umxACE Cholesky model with covariates.

References

- Neale, M. C., & Martin, N. G. (1989). The effects of age, sex, and genotype on self-report drunkenness following a challenge dose of alcohol. Behavior Genetics, 19, 63-78. doi:10.1007/BF01065884

Schwabe, I., Boomsma, D. I., Zeeuw, E. L., & Berg, S. M. (2015). A New Approach to Handle Missing Covariate Data in Twin Research : With an Application to Educational Achievement Data. Behavior Genetics. doi:10.1007/s10519-015-9771-1

See Also

Other Twin Modeling Functions: plot.MxModel, umxACESexLim, umxACE, umxCF_SexLim, umxCP, umxGxE_window, umxGxE, umxIP, umxPlotACEcov, umxPlotCP, umxPlotGxE, umxPlotIP, umxSummaryACEcov, umxSummaryACE, umxSummaryCP, umxSummaryGxE, umxSummaryIP, umx

Examples

# NOT RUN {
require(umx)
data(twinData)
# replicate age to age1 & age2
twinData$age1 = twinData$age2 = twinData$age
selDVs  = c("bmi") # Set the DV
selCovs = c("age") # Set the IV
selVars = umx_paste_names(selDVs, covNames = selCovs, sep = "", suffixes = 1:2)
# 80 rows so example runs fast
mzData = subset(twinData, zygosity == "MZFF", selVars)[1:80, ]
dzData = subset(twinData, zygosity == "DZFF", selVars)[1:80, ]
m1 = umxACEcov(selDVs = selDVs, selCovs = selCovs,
   dzData = dzData, mzData = mzData, suffix = "", autoRun = TRUE
)
umxSummary(m1)
plot(m1)
# ====================
# = A bivariate test =
# ====================
selDVs  = c("ht", "wt") # Set the DV
selCovs = c("age") # Set the IV
selVars = umx_paste_names(selDVs, covNames = selCovs, sep = "", suffixes = 1:2)
# 80 rows so example runs fast enough on CRAN
mzData = subset(twinData, zygosity == "MZFF", selVars)[1:80, ]
dzData = subset(twinData, zygosity == "DZFF", selVars)[1:80, ]
m1 = umxACEcov(selDVs = selDVs, selCovs = selCovs,
   dzData = dzData, mzData = mzData, suffix = "", autoRun = TRUE
)


# Univariate bmi without covariate of age for comparison
m2     = umxACE(selDVs = selDVs, dzData = dzData, mzData = mzData, suffix="")
x      = umx_residualize("bmi", "age", suffixes=1:2, twinData)
mzData = subset(x, zygosity == "MZFF", selVars)[1:80, ]
dzData = subset(x, zygosity == "DZFF", selVars)[1:80, ]
m3     = umxACE(selDVs = selDVs, dzData = dzData, mzData = mzData, suffix="")



# }