Can't replicate sem package in R

I'm slowly converting to OpenMX because of its fiml capabilities. I recently built two models that are shown in the enclosed attachments. You will notice that the correlation between T and P is identical in both models (whether S or D is used). However, when I try to replicate these results in OpenMX, I don't get identical results; they're usually about .04 different, which is quite significant for what I'm doing.

Here's my openMX code:

sem.model.S = mxModel("Two Factor Model Path Specification",
type="RAM",
dd,
manifestVars = names(data),
latentVars = c("T", "P"),
#### residual variances of observed
mxPath(
from=names(data)[-4],
arrows=2,
free=c(FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE),
values=1,
labels=c("z1","z2","z3",paste("e", 1:6, sep=""))
),
# exogenous variances and covariance
mxPath(
from=c("S", "P", "T"),
arrows=2,
all=TRUE,
free=c(TRUE, TRUE, TRUE, TRUE, FALSE, TRUE, TRUE, TRUE, FALSE),
values=rep(1, times=9),
labels=c("varS", "cov1", "cov2",
"cov1", "varP", "cov3",
"cov2", "cov3", "varT")
),
# factor loadings for x variables
mxPath(
from="T",
to=c("X1","X2","X3"),
arrows=1,
free=c(TRUE,TRUE,TRUE),
values=c(1,1,1),
labels=c("l1","l2","l3")
),
#factor loadings for y variables
mxPath(
from="P",
to=c("Y1","Y2","Y3"),
arrows=1,
free=c(TRUE,TRUE,TRUE),
values=c(1,1,1),
labels=c("l4","l5","l6")
),
##### loadings for S
mxPath(
from=names(data)[1:3],
to=c("S"),
arrows=1,
free=TRUE,
values=c(1,1,1),
labels=c("z1l", "z2l", "z3l")
),

#means
mxPath(
from="one",
to=c("Interview", "Personality", "IQ", "X1","X2","X3","Y1","Y2","Y3","S","T","P"),
arrows=1,
free=c(rep(TRUE, times=10), FALSE, FALSE),
values=c(rep(1, times=10), 0, 0),
labels=c("meanInt", "meanPers", "meanIQ","meanx1","meanx2","meanx3",
"meany1","meany2","meany3","meanS",NA, NA)
)

)

The other model is nearly identical, except I replace "S" with "D"....could it be because I'm estimating means now when before I was using a correlation matrix? S and D are on different scales, but I wouldn't think it would matter that much.

Thanks!