# Options

# Surpress scientific notations, digits and lines

options(scipen=999, digits=10, max.print=99999999)


library(lavaan)


#CFA Model Covariance Matrix

CFA.Model.cov<-'
F1 =~ 0.8*x1 + 0.8*x2 + 0.8*x3
F2 =~ 0.8*x4 + 0.8*x5 + 0.8*x6
F1 ~~ 1*F1
F2 ~~ 1*F2
F1 ~~ 0.5*F2
x1 ~~ 0.36*x1
x2 ~~ 0.36*x2
x3 ~~ 0.36*x3
x4 ~~ 0.36*x4
x5 ~~ 0.36*x5
x6 ~~ 0.36*x6
'

cov.lower<- '
1
0 1
0 0 1
0 0 0 1
0 0 0 0 1
0 0 0 0 0 1
'

cov.matrix<-getCov(cov.lower, names = c("x1", "x2", "x3", "x4", "x5", "x6"))


FIT.cov<-cfa(CFA.Model.cov, sample.cov=cov.matrix, sample.nobs=5000, mimic="EQS")
#estimator: "MLM"

summary(FIT.cov, standardized = TRUE)

FIT.cov@implied

FIT.cov@implied[[1]]

fitted(FIT.cov)

cov.matrix.pf<-matrix(unlist(FIT.cov@implied[[1]]), nrow=6, ncol=6)

cov.matrix.pf<-fitted(FIT.cov)$cov

#CFA Model Covariance Matrix

CFA.Model.pf<-'
F1 =~ x1 + x2 + x3
F2 =~ x4 + x5 + x6
'

FIT.cov.pf<-cfa(CFA.Model.pf, sample.cov=cov.matrix.pf, sample.nobs=5000, mimic="EQS")
#estimator: "MLM"

summary(FIT.cov.pf, standardized = TRUE)
fitMeasures(FIT.cov.pf)