Prints the results of lavaan_rerun().
Usage
# S3 method for lavaan_rerun
print(x, ...)Arguments
- x
The output of
lavaan_rerun().- ...
Other arguments. They will be ignored.
Author
Shu Fai Cheung https://orcid.org/0000-0002-9871-9448
Examples
library(lavaan)
dat <- pa_dat
# For illustration only, select only the first 50 cases
dat <- dat[1:50, ]
# The model
mod <-
"
m1 ~ iv1 + iv2
dv ~ m1
"
# Fit the model
fit <- lavaan::sem(mod, dat)
summary(fit)
#> lavaan 0.6.17 ended normally after 1 iteration
#>
#> Estimator ML
#> Optimization method NLMINB
#> Number of model parameters 5
#>
#> Number of observations 50
#>
#> Model Test User Model:
#>
#> Test statistic 1.768
#> Degrees of freedom 2
#> P-value (Chi-square) 0.413
#>
#> Parameter Estimates:
#>
#> Standard errors Standard
#> Information Expected
#> Information saturated (h1) model Structured
#>
#> Regressions:
#> Estimate Std.Err z-value P(>|z|)
#> m1 ~
#> iv1 -0.159 0.166 -0.954 0.340
#> iv2 0.525 0.162 3.241 0.001
#> dv ~
#> m1 0.350 0.161 2.169 0.030
#>
#> Variances:
#> Estimate Std.Err z-value P(>|z|)
#> .m1 0.901 0.180 5.000 0.000
#> .dv 1.423 0.285 5.000 0.000
#>
# Fit the model n times. Each time with one case removed.
fit_rerun <- lavaan_rerun(fit, parallel = FALSE)
#> The expected CPU time is 1.8 second(s).
#> Could be faster if run in parallel.
fit_rerun
#> === lavaan_rerun Output ===
#> Call:
#> lavaan_rerun(fit = fit, parallel = FALSE)
#> Number of reruns: 50
#> Number of reruns that converged (solution found): 50
#> Number of reruns that failed to converge (solution not found): 0
#> Number of reruns that passed post.check of lavaan: 50
#> Number of reruns that failed post.check of lavaan: 0
#> Number of reruns that both converged and passed post.check: 50
#> Number of reruns that either did not converge or failed post.check: 0