Extract labelled parameters of lavaan objects

extract_param(lavaan_object, printp = FALSE)

Arguments

lavaan_object

lavaan object.

printp

If TRUE convert into easily readable p values.

Value

This function returns a tibble with labelled parameters.

References

David Robinson and Alex Hayes (2019). broom: Convert Statistical Analysis Objects into Tidy Tibbles. R package version 0.5.2. https://CRAN.R-project.org/package=broom

Examples

# First create a lavaan object bi_lcsm_01 <- fit_bi_lcsm(data = data_bi_lcsm, var_x = names(data_bi_lcsm)[2:4], var_y = names(data_bi_lcsm)[12:14], model_x = list(alpha_constant = TRUE, beta = TRUE, phi = FALSE), model_y = list(alpha_constant = TRUE, beta = TRUE, phi = TRUE), coupling = list(delta_lag_xy = TRUE, xi_lag_yx = TRUE) )
#> Warning: lavaan WARNING: #> The variance-covariance matrix of the estimated parameters (vcov) #> does not appear to be positive definite! The smallest eigenvalue #> (= 1.058210e-15) is close to zero. This may be a symptom that the #> model is not identified.
# Now extract parameter estimates extract_param(bi_lcsm_01)
#> # A tibble: 22 × 8 #> label estimate std.error statistic p.value std.lv std.all std.nox #> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 gamma_lx1 21.1 0.0377 560. 0 29.3 29.3 29.3 #> 2 sigma2_lx1 0.517 0.0417 12.4 0 1 1 1 #> 3 sigma2_ux 0.171 0.0109 15.6 0 0.171 0.248 0.248 #> 4 alpha_g2 -0.250 0.856 -0.292 0.770 -0.383 -0.383 -0.383 #> 5 sigma2_g2 0.426 0.0455 9.38 0 1 1 1 #> 6 sigma_g2lx1 0.143 0.0300 4.76 0.00000193 0.304 0.304 0.304 #> 7 beta_x -0.0905 0.0642 -1.41 0.159 -0.101 -0.101 -0.101 #> 8 gamma_ly1 5.03 0.0300 168. 0 10.4 10.4 10.4 #> 9 sigma2_ly1 0.235 0.0275 8.53 0 1 1 1 #> 10 sigma2_uy 0.177 0.0118 15.0 0 0.177 0.429 0.429 #> # … with 12 more rows