DTB5H6allg <-readLowTriMat("corrs.dat", no.var=14)
n_allg <-c(220,223,293,369,432,364,101,274,95,128,70,132,304,1063,
           180,241,380,304,1448,207,509,507,764,743,340,266,197,637,82,
           44,46,298,544,533,273,246,296,123,290,216,500,819,611,302,501,
           828,164,232,200,287,397,300,789,341,279,770,150,170,368,159,
           245,199,202,80,504,277,892,251,546,198,232,246,232,1568,487,278,
           179,401,180,260,389,676,305,249,107,326,256,443,663,305,316,325,
           394,481,66,1108,221,311,256,634,638,242,192,957,256,680,300,316)
randomDTB5H6<-tssem1(DTB5H6allg,n_allg,method="REM",RE.type="Zero", acov="weighted") 

DTB5H6Gk2 <- "## Factor loadings
          DT =~ M+N+P+FFMC+FFMA+HH+HA+HC
          Alpha =~ FFMC+FFMA+FFMN+HE+HA+HC
          Beta =~ N+FFMO+FFME+HX+HO
## 2nd order general factor
          G =~ Alpha + Beta
## Fix the variance of G at 1
          G ~~ 1*G"

## Display the model
plot(DTB5H6Gk2)

## Convert model to RAM
RAM <- lavaan2RAM(DTB5H6Gk2, obs.variables=c("M","N","P","FFMO","FFMC","FFME","FFMA","FFMN","HH","HE","HX","HA","HC","HO"), std.lv=FALSE)
RAM

fitDTB5H6Gk2 <- tssem2(randomDTB5H6, RAM=RAM, intervals="LB")
summary(fitDTB5H6Gk2)