Problem with the new OSMASEM-Function

Hi Mike,
Thanks for this great example. I'm still learning how to use the OSMASEM approach which seems very useful. I am able to successfully run the analyses, but I was wondering if when testing moderating effects, do I have to populate the Ax matrix for all paths in my model, or can I just estimate the moderating effects for only the paths that I'm interested in testing the moderating effect for?
Thanks,
Sergio

Hi Mike,
I'm trying to estimate this model in OSMASEM, and I can't. I get this error:

> M0 <- create.vechsR(A0=RAM4$A, S0=RAM4$S, F0=RAM4$F)
> ## Create heterogeneity variances
> T0 <- create.Tau2(RAM=RAM4, RE.type="Symm")
> mx.fit0 <- osmasem(model.name="No moderator", Mmatrix=M0, Tmatrix=T0, data=my.df)

Warning message:
The following error occurred while evaluating the subexpression '`No moderator.Tau2` + `No moderator.V`' during the evaluation of 'expCov' in model 'No moderator' : non-conformable arrays

model4<- 'out =~ PAT2out*PAT + CIT2out*CIT
+ out ~ SIZE2OUT*SIZ + IO2OUT*IO + CON2OUT*CON + RD2Out*RD
+ RD ~ SIZE2RD*SIZ + IO2RD*IO + CON2RD*CON
+ IO ~~ p10*SIZ
+ IO ~~ p11*CON
+ SIZ ~~ 1*SIZ
+ IO ~~ 1*IO
+ CON ~~ 1*CON
+ RD ~~ p20*RD
+ out ~~ p21*out
+ PAT ~~ p22*PAT
+ CIT ~~ p23*CIT'
plot(model4, color="yellow", layout = "tree2")
RAM4 <- lavaan2RAM(model4, obs.variables=c("IO","SIZ","CON","RD","PAT","CIT"), std.lv = FALSE)

I can estimate this same model in TSSEM without any problems:
my.vec <- readStackVec("matrix1.dat")
my.vec <- lapply(my.vec,function(x)
{dimnames(x) <- list(c("IO","SIZ","CON","RD","PAT","CIT"),
c("IO","SIZ","CON","RD","PAT","CIT"))
x})

f<-c(0,0,0,0,"0.2*g_E","0.2*g_O")
F<-matrix(f,ncol = 1,nrow = 6)
F

A1 <- matrix(c(0,0,0,0,0,0,
0,0,0,0,0,0,
0,0,0,0,0,0,
"0.3*IO2RD","0.3*IO2SIZ","0.3*CON2RD",0,0,0,
0,0,0,0,0,0,
0,0,0,0,0,0),
nrow=6, ncol=6, byrow=TRUE)
A1
A<-rbind(cbind(A1, F), matrix (c("0.2*IO2out","0.2*SIZ2out","0.2*CON2OUT","0.2*RD2OUT",0,0,0), ncol=7, nrow=1))
A
dimnames(A)<-list(c("IO","SIZ","CON","RD","PAT","CIT","out"), c("IO","SIZ","CON","RD","PAT","CIT","out"))
A
phi<-matrix(c("0.3*e5"),nrow = 1,ncol = 1)
psi<-matrix(c(1,"0.3*e4","0.3*e6",0,0,0,
"0.3*e4",1,0,0,0,0,
"0.3*e6",0,1,0,0,0,
0,0,0,"0.3*e1",0,0,
0,0,0,0,"0.3*e2",0,
0,0,0,0,0,"0.3*e3"),
nrow=6, ncol=6, byrow=TRUE)
S<-bdiagMat(list(psi,phi))
dimnames(S)<-list(c("IO","SIZ","CON","RD","PAT","CIT","out"), c("IO","SIZ","CON","RD","PAT","CIT","out"))
S
FM<-create.Fmatrix(c(1,1,1,1,1,1,0), as.mxMatrix = FALSE)
dimnames(FM)<-list(c("IO","SIZ","CON","RD","PAT","CIT"), c("IO","SIZ","CON","RD","PAT","CIT","out"))
FM

Random1 <- tssem1(my.vec, my.n, method = "REM")
summary(Random1)
Random2<-tssem2(Random1, Amatrix = A,Smatrix = S,Fmatrix = FM, model.name = "IBTmediator",
diag.constraints = FALSE)
summary(Random2)

Do you know why I can't estimate this model in OSMASEM?

Thanks for the amazing software and approach. I would really appreciate your help with this.

Thanks,
Sergio

Hi Mike;

Thank you for your help. Indeed, I was missing "Saturated = TRUE" command in summary(), which prevented me from comparing OSMASEM results with tssem results. I have some questions regarding OSMASEM with a moderator.

I am testing one moderator on five relations in my model (RAM1$A). The results show df=-1 and consequently TLI=1 and RMSEA=0. Should df and goodness-of-fit indices be interpreted the same way as in tssem? Meaning that should df always be positive in OSMASEM? and can I interpret RMSEA and TLI the same as in tssem? Also, if df should be kept positive, is it ok to remove some of the moderations from Ax matrix?

Thank you
Hamed

Hi Mike;

Thank you for your response. ANOVA() is very helpful. It clarified the issue for me.

Best
Hamed

Thanks for your help!