I generating a PA model using `lavaan`

, so I would like to evaluate my model using fit indexes but residuals too.

Reading about I found this example:

```
library(lavaan)
# The Holzinger and Swineford (1939) example
HS.model <- ' visual =~ x1 + x2 + x3
textual =~ x4 + x5 + x6
speed =~ x7 + x8 + x9 '
fit <- lavaan(HS.model, data=HolzingerSwineford1939,
auto.var=TRUE, auto.fix.first=TRUE,
auto.cov.lv.x=TRUE)
summary(fit, fit.measures=TRUE)
# View Residuals (documentation in the lavaan-class help file)
resid(fit, type='normalized')
and the result was:
$type
[1] "normalized"
$cov
x1 x2 x3 x4 x5 x6 x7 x8 x9
x1 0.000
x2 -0.493 0.000
x3 -0.125 1.539 0.000
x4 1.159 -0.214 -1.170 0.000
x5 -0.153 -0.459 -2.606 0.070 0.000
x6 0.983 0.507 -0.436 -0.130 0.048 0.000
x7 -2.423 -3.273 -1.450 0.625 -0.617 -0.240 0.000
x8 -0.655 -0.896 -0.200 -1.162 -0.624 -0.375 1.170 0.000
x9 2.405 1.249 2.420 0.808 1.126 0.958 -0.625 -0.504 0.000
$mean
x1 x2 x3 x4 x5 x6 x7 x8 x9
0 0 0 0 0 0 0 0 0
```

How would I interpret these? Would somebody send me a reference? I am looking for an interpretation of this in `lavaan`

and could not find good material.