NA
Examples
HS.model <- 'visual =~ x1 + x2 + x3'
library(lavaan)
fit <- lavaan::cfa(model = HS.model, data = HolzingerSwineford1939)
foo(fit)
#> lavaan 0.6-12 ended normally after 23 iterations
#>
#> Estimator ML
#> Optimization method NLMINB
#> Number of model parameters 6
#>
#> Number of observations 301
#>
#> Model Test User Model:
#>
#> Test statistic 0.000
#> Degrees of freedom 0
#>
#> Parameter Estimates:
#>
#> Standard errors Standard
#> Information Expected
#> Information saturated (h1) model Structured
#>
#> Latent Variables:
#> Estimate Std.Err z-value P(>|z|)
#> visual =~
#> x1 1.000
#> x2 0.778 0.141 5.532 0.000
#> x3 1.107 0.214 5.173 0.000
#>
#> Variances:
#> Estimate Std.Err z-value P(>|z|)
#> .x1 0.835 0.118 7.064 0.000
#> .x2 1.065 0.105 10.177 0.000
#> .x3 0.633 0.129 4.899 0.000
#> visual 0.524 0.130 4.021 0.000
#>