Greetings, fairly new student of OpenMx here. I've successfully run a univariate twin model with confidence intervals thanks to mxCI, but in the quadvariate script below (obtained from http://ibg.colorado.edu/cdrom2014/bartels/Multivariate/Trivariate.R), I don't know where to put the mxCI command to request CIs for A/V, C/V, and E/V. The output is in the form of a matrix too, so I am unsure how to proceed. Any assistance would be greatly appreciated.
Matrices declared to store a, c, and e Path Coefficients
pathA <- mxMatrix( type="Lower", nrow=nv, ncol=nv, free=TRUE,
values=svPa, labels=labLower("a",nv), lbound=lbPa, name="a" )
pathC <- mxMatrix( type="Lower", nrow=nv, ncol=nv, free=TRUE,
values=svPa, labels=labLower("c",nv), lbound=lbPa, name="c" )
pathE <- mxMatrix( type="Lower", nrow=nv, ncol=nv, free=TRUE,
values=svPa, labels=labLower("e",nv), lbound=lbPa, name="e" )
Matrices generated to hold A, C, and E computed Variance Components
covA <- mxAlgebra( expression=a %% t(a), name="A" )
covC <- mxAlgebra( expression=c %% t(c), name="C" )
covE <- mxAlgebra( expression=e %*% t(e), name="E" )
Algebra to compute total variances and standard deviations (diagonal only)
covP <- mxAlgebra( expression=A+C+E, name="V" )
matI <- mxMatrix( type="Iden", nrow=nv, ncol=nv, name="I")
invSD <- mxAlgebra( expression=solve(sqrt(I*V)), name="iSD")
Algebra for expected Mean and Variance/Covariance Matrices in MZ & DZ twins
meanG <- mxMatrix( type="Full", nrow=1, ncol=ntv, free=TRUE,
values=svMe, labels=labFull("me",1,nv), name="expMean" )
covMZ <- mxAlgebra( expression= rbind( cbind(V, A+C), cbind(A+C, V)), name="expCovMZ" )
covDZ <- mxAlgebra( expression= rbind( cbind(V, 0.5%x%A+C), cbind(0.5%x%A+C, V)), name="expCovDZ" )
Data objects for Multiple Groups
dataMZ <- mxData( observed=mzData, type="raw" )
dataDZ <- mxData( observed=dzData, type="raw" )
Objective objects for Multiple Groups
objMZ <- mxFIMLObjective( covariance="expCovMZ", means="expMean", dimnames=selVars )
objDZ <- mxFIMLObjective( covariance="expCovDZ", means="expMean", dimnames=selVars )
Combine Groups
pars <- list( pathA, pathC, pathE, covA, covC, covE, covP, matI, invSD, meanG )
modelMZ <- mxModel( pars, covMZ, dataMZ, objMZ, name="MZ" )
modelDZ <- mxModel( pars, covDZ, dataDZ, objDZ, name="DZ" )
minus2ll <- mxAlgebra( expression=MZ.objective + DZ.objective, name="m2LL" )
obj <- mxAlgebraObjective( "m2LL" )
CholAceModel <- mxModel( "CholACE", pars, modelMZ, modelDZ, minus2ll, obj )
------------------------------------------------------------------------------
RUN GENETIC MODEL
Run Cholesky Decomposition ACE model
CholAceFit <- mxRun(CholAceModel)