hi,
I have following data and code;
cov <-
c
(1.670028
,-1.197685
,-2.931445,-1.197685,1.765646,3.883839,-2.931445,3.883839,12.050816)
cov.matrix <- matrix(cov, 3, 3, dimnames=list(c("y1","x1","x2"),
c("y1","x1","x2")))
path.model <- specify.model()
x1 -> y1, x1-y1
x2 <-> x1, x2-x1
x2 <-> x2, x2-x2
x1 <-> x1, x1-x1
y1 <-> y1, y1-y1
x2 -> y1, x2-y1
summary(sem(path.model, cov.matrix, N = 422))
and I get following results;
Model Chisquare = 12.524 Df = 1 Pr(>Chisq) = 0.00040179
Chisquare (null model) = 812.69 Df = 3
Goodness-of-fit index = 0.98083
Adjusted goodness-of-fit index = 0.885
RMSEA index = 0.16545 90% CI: (0.09231, 0.25264)
Bentler-Bonnett NFI = 0.98459
Tucker-Lewis NNFI = 0.9573
Bentler CFI = 0.98577
SRMR = 0.027022
BIC = 6.4789
Parameter Estimates
Estimate Std Error z value Pr(>|z|)
x1-y1 -0.67833 0.033967 -19.970 0 y1 <--- x1
x2-x1 3.88384 0.293743 13.222 0 x1 <--> x2
x2-x2 12.05082 0.831569 14.492 0 x2 <--> x2
x1-x1 1.76565 0.121839 14.492 0 x1 <--> x1
y1-y1 0.85761 0.059124 14.505 0 y1 <--> y1
Iterations = 0
Now I wonder why the chi-square value is so bad and what Pr(>Chisq)
tells me.
Can anyone help me on this?
When I allow the path x2 -> y1 I get of course a good fit, but the
path coefficient of x2 -> y1 is pretty low (-0.084653), so I thought I
can restrict that one to zero.
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