The Missing Coefficients in metaSEM

Hi Mike,
I am running the metaSEM for a mediation model. The results seem good. But when I tried to extrcat the cofficients, there is a problem. In this model, there are three indepent variables and there should be three correlation coefficients between those three variables as well. But in the summary and coef results, there is only one correlation coefficients, cor = 0.43. I want to report all coefficients in my meta-analysis. So could you please check my code and tell me how to read those three correlation coefficients?

Here is my code.

library(metaSEM)
library(lavaan)

x1 <- matrix(c(
1,0.49,0.5,0.23,0.21,
0.49,1,0.46,0.13,0.17,
0.5,0.46,1,0.29,0.49,
0.23,0.13,0.29,1,0.58,
0.21,0.17,0.49,0.58,1),
nrow = 5, ncol = 5, byrow = TRUE, dimnames = list(c("SOP","OOP","SPP","RUM","DEP"),c("SOP","OOP","SPP","RUM","DEP")))

x2 <- matrix(c(
1,0.49,0.5,0.23,0.24,
0.49,1,0.46,0.13,0.12,
0.5,0.46,1,0.29,0.47,
0.23,0.13,0.29,1,0.55,
0.24,0.12,0.47,0.55,1),
nrow = 5, ncol = 5, byrow = TRUE, dimnames = list(c("SOP","OOP","SPP","RUM","DEP"),c("SOP","OOP","SPP","RUM","DEP")))

x3 <- matrix(c(
1,0.42,0.49,0.23,-0.17,
0.42,1,0.41,0.22,0.05,
0.49,0.41,1,0.27,0.3,
0.23,0.22,0.27,1,0.4,
-0.17,0.05,0.3,0.4,1),
nrow = 5, ncol = 5, byrow = TRUE, dimnames = list(c("SOP","OOP","SPP","RUM","DEP"),c("SOP","OOP","SPP","RUM","DEP")))

x4 <- matrix(c(
1,0.5,0.54,0.21,0.15,
0.5,1,0.36,0.11,0.1,
0.54,0.36,1,0.41,0.39,
0.21,0.11,0.41,1,0.54,
0.15,0.1,0.39,0.54,1),
nrow = 5, ncol = 5, byrow = TRUE, dimnames = list(c("SOP","OOP","SPP","RUM","DEP"),c("SOP","OOP","SPP","RUM","DEP")))

x5 <- matrix(c(
1,0.44,0.47,0.26,0.07,
0.44,1,0.44,0.22,0.06,
0.47,0.44,1,0.38,0.4,
0.26,0.22,0.38,1,0.53,
0.07,0.06,0.4,0.53,1),
nrow = 5, ncol = 5, byrow = TRUE, dimnames = list(c("SOP","OOP","SPP","RUM","DEP"),c("SOP","OOP","SPP","RUM","DEP")))

x6 <- matrix(c(
1,0.31,0.41,0.26,0.17,
0.31,1,0.23,0.03,-0.11,
0.41,0.23,1,0.49,0.47,
0.26,0.03,0.49,1,0.66,
0.17,-0.11,0.47,0.66,1),
nrow = 5, ncol = 5, byrow = TRUE, dimnames = list(c("SOP","OOP","SPP","RUM","DEP"),c("SOP","OOP","SPP","RUM","DEP")))

x7 <- matrix(c(
1,0.46,0.38,0.18,0.03,
0.46,1,0.3,0.06,0.06,
0.38,0.3,1,0.29,0.3,
0.18,0.06,0.29,1,0.56,
0.03,0.06,0.3,0.56,1),
nrow = 5, ncol = 5, byrow = TRUE, dimnames = list(c("SOP","OOP","SPP","RUM","DEP"),c("SOP","OOP","SPP","RUM","DEP")))

x8 <- matrix(c(
1,0.46,0.38,0.17,0.03,
0.46,1,0.3,0.1,0.06,
0.38,0.3,1,0.26,0.3,
0.17,0.1,0.26,1,0.42,
0.03,0.06,0.3,0.42,1),
nrow = 5, ncol = 5, byrow = TRUE, dimnames = list(c("SOP","OOP","SPP","RUM","DEP"),c("SOP","OOP","SPP","RUM","DEP")))

x9 <- matrix(c(
1,0.33,0.48,0.34,0.21,
0.33,1,0.08,0.05,-0.06,
0.48,0.08,1,0.58,0.41,
0.34,0.05,0.58,1,0.37,
0.21,-0.06,0.41,0.37,1),
nrow = 5, ncol = 5, byrow = TRUE, dimnames = list(c("SOP","OOP","SPP","RUM","DEP"),c("SOP","OOP","SPP","RUM","DEP")))

x10 <- matrix(c(
1,0.33,0.48,0.07,0.21,
0.33,1,0.08,0.13,-0.06,
0.48,0.08,1,0.35,0.41,
0.07,0.13,0.35,1,0.76,
0.21,-0.06,0.41,0.76,1),
nrow = 5, ncol = 5, byrow = TRUE, dimnames = list(c("SOP","OOP","SPP","RUM","DEP"),c("SOP","OOP","SPP","RUM","DEP")))

x11 <- matrix(c(
1,0.43,0.47,0.22,0.13,
0.43,1,0.38,0.14,0.09,
0.47,0.38,1,0.36,0.34,
0.22,0.14,0.36,1,0.52,
0.13,0.09,0.34,0.52,1),
nrow = 5, ncol = 5, byrow = TRUE, dimnames = list(c("SOP","OOP","SPP","RUM","DEP"),c("SOP","OOP","SPP","RUM","DEP")))

my.df1<-list("1"=x1,"2"=x2,"3"=x3,"4"=x4,"5"=x5,"6"=x6,"7"=x7,"8"=x8,"9"=x9,"10"=x10,"11"=x11)
my.df1

n <-c(150,150,155,279,224,140,305,305,50,50,213)
n

fixed1 <- tssem1(my.df1, n, method="FEM")
summary(fixed1)

model <- "
RUM~SPP2RUM*SPP + SOP2RUM*SOP + OOP2RUM*OOP
DEP~SPP2DEP*SPP + SOP2DEP*SOP + OOP2DEP*OOP + RUM2DEP*RUM
SOP~~1*SOP
OOP~~1*OOP
SPP~~1*SPP
SOP~~cor*OOP
SOP~~cor*SPP
OOP~~cor*SPP
RUM~~var_RUM*RUM
DEP~~var_DEP*DEP"

RAM <- lavaan2RAM(model, obs.variables=c("SOP","OOP","SPP","RUM","DEP"))
RAM
A1 <- RAM$A
S1 <- RAM$S
fixed2 <- tssem2(fixed1, Amatrix=A1, Smatrix=S1, diag.constraints=TRUE, intervals.type="LB", model.name="perfectionism rum dep")
summary(fixed2)
coef(fixed2)
vcov(fixed2)

Many thanks,
Yu Xie