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I've been trying to replicate a model by Preacher (2006). I've enclosed the graphic of the model. And here's my code:
multiRegModelPr2 <- mxModel("Preacher 2",
type="RAM",
mxData(
observed=data,
type="raw"
),
manifestVars=c("x", "y", "z"),
latentVars = c("z1", "z2", "z3"),
# variance paths
mxPath(
from=c("x", "y", "z", "z1", "z2", "z3"),
arrows=2,
free=c(T,T,T,F,F,F),
values = c(.5, .5, .5, 1, 1, 1),
labels=c("d1", "d2", "d3", NA, NA, NA)
),
# covariance of x and z
mxPath(
from="z2",
to="z3",
arrows=2,
free=TRUE,
values=0.2,
labels="covxz"
),
# regression weights from Z1
mxPath(
from=c("z1"),
to=c("z","y", "x"),
arrows=1,
free=TRUE,
values=.5,
labels=c("bz", "by", "bx")
),
# regression weights from Z2
mxPath(
from=c("z2"),
to=c("x"),
arrows=1,
free=TRUE,
values=.5,
labels=c("bx2")
),
# regression weights from Z3
mxPath(
from=c("z3"),
to=c("y"),
arrows=1,
free=TRUE,
values=.5,
labels=c("by2")
),
# means and intercepts
mxPath(
from="one",
to=c("x", "y", "z", "z1", "z2", "z3"),
arrows=1,
free=c(T,T,T,F,F,F),
values=c(.5, .5, .5, 0, 0,0),
labels=c("meanx", "beta0", "meanz", NA, NA,NA)
)
) # close model #
I'm getting really weird estimates that disagree with SAS estimates. Any help would be appreciated! Thanks!