In a ACE bivariate Cholesky, any ideas why confidence intervals for a shared environmental correlation would be returned as (-1.00, 1.00)? My syntax is included below. The model converged without any errors.
bivACEModel <- mxModel("bivACE", mxModel("ACE", # Matrices a, c, and e to store a, c, and e path coefficients mxMatrix( type="Lower", nrow=nv, ncol=nv, free=TRUE, values=.8, labels=c("a11","a21","a22"), name="a" ), mxMatrix( type="Lower", nrow=nv, ncol=nv, free=TRUE, values=.8, labels=c("c11","c21","c22"),name="c" ), mxMatrix( type="Lower", nrow=nv, ncol=nv, free=TRUE, values=.8, labels=c("e11","e21","e22"),name="e" ), # Matrices A, C, and E compute variance components mxAlgebra( expression=a %*% t(a), name="A" ), mxAlgebra( expression=c %*% t(c), name="C" ), mxAlgebra( expression=e %*% t(e), name="E" ), # Algebra to compute total variances and standard deviations (diagonal only) mxAlgebra( expression=A+C+E, name="V" ), mxMatrix( type="Iden", nrow=nv, ncol=nv, name="I"), mxAlgebra( expression=solve(sqrt(I*V)), name="iSD"), mxAlgebra(iSD %*% a, name="sta"), mxAlgebra(iSD %*% c, name="stc"), mxAlgebra(iSD %*% e, name="ste"), mxAlgebra(A/V, name="StandardizedA"), mxAlgebra(C/V, name="StandardizedC"), mxAlgebra(E/V, name="StandardizedE"), mxAlgebra(solve(sqrt(I*A)) %&% A, name="CorA"), mxAlgebra(solve(sqrt(I*C)) %&% C, name="CorC"), mxAlgebra(solve(sqrt(I*E)) %&% E, name="CorE"), mxAlgebra(solve(sqrt(I*V)) %&% V, name="CorP"), ## Note that the rest of the mxModel statements do not change for bivariate/multivariate case # Matrix & Algebra for expected means vector mxMatrix( type="Full", nrow=1, ncol=nv, free=TRUE, values= 20, name="Mean" ), mxAlgebra( expression= cbind(Mean,Mean), name="expMean"), # Algebra for expected variance/covariance matrix in MZ mxAlgebra( expression= rbind ( cbind(A+C+E , A+C), cbind(A+C , A+C+E)), name="expCovMZ" ), # Algebra for expected variance/covariance matrix in DZ, note use of 0.5, converted to 1*1 matrix mxAlgebra( expression= rbind ( cbind(A+C+E , 0.5%x%A+C), cbind(0.5%x%A+C , A+C+E)), name="expCovDZ" ) ), mxModel("MZ", mxData( observed=mzData, type="raw" ), mxFIMLObjective( covariance="ACE.expCovMZ", means="ACE.expMean", dimnames=selVars ) ), mxModel("DZ", mxData( observed=dzData, type="raw" ), mxFIMLObjective( covariance="ACE.expCovDZ", means="ACE.expMean", dimnames=selVars ) ), mxAlgebra( expression=MZ.objective + DZ.objective, name="minus2sumloglikelihood" ), mxAlgebraObjective("minus2sumloglikelihood"), mxCI(c('ACE.sta', 'ACE.stc', 'ACE.ste')), mxCI(c('ACE.StandardizedA', 'ACE.StandardizedC', 'ACE.StandardizedE')), mxCI(c('ACE.CorA', 'ACE.CorC', 'ACE.CorE', 'ACE.CorP')) ) bivACEFit <- mxRun(bivACEModel) bivACESumm <- summary(bivACEFit) bivACESumm