This function takes a lavaan model with standardized parameters and simulates latent scores, errors, disturbances, and observed scores.

sim_standardized(
  m,
  n = 1000,
  observed = TRUE,
  latent = TRUE,
  errors = TRUE,
  factor_scores = FALSE,
  composites = FALSE,
  matrices = FALSE,
  ...
)

Arguments

m

Structural model represented by lavaan syntax

n

Number of simulated cases

observed

Include observed variables

latent

Include latent variables

errors

Include observed error and latent disturbances variables

factor_scores

Include factor score variables

composites

Include composite variables

matrices

Include matrices as attribute of tibble

...

Arguments passed to `simstandardized_matrices`

Value

tibble with standardized data

Details

This function supports the `~` operator for regressions, the `~~` for covariances (but not variances), and the `=~` latent variable loadings. It does not support intercepts (e.g,. `y ~ 1`), thresholds, scaling factors, formative factors, or equality constraints.

Examples

library(simstandard)
# Lavaan model
m = "Latent_1 =~ 0.8 * Ob_1 + 0.7 * Ob_2 + 0.4 * Ob_3"

# simulate 10 cases
sim_standardized(m, n = 10)
#> # A tibble: 10 × 7
#>      Ob_1    Ob_2    Ob_3 Latent_1 e_Ob_1 e_Ob_2  e_Ob_3
#>     <dbl>   <dbl>   <dbl>    <dbl>  <dbl>  <dbl>   <dbl>
#>  1 -0.187  0.936   0.0448   0.0558 -0.231  0.896  0.0224
#>  2  2.30   2.62    0.780    2.35    0.422  0.974 -0.159 
#>  3  0.663 -0.332  -0.210    0.467   0.289 -0.660 -0.397 
#>  4  0.992  0.219  -0.138    1.02    0.176 -0.495 -0.546 
#>  5 -0.225  0.0464 -0.286   -1.01    0.582  0.752  0.117 
#>  6 -1.37  -0.205  -0.509   -1.02   -0.558  0.508 -0.102 
#>  7  0.445 -0.654  -0.410    0.825  -0.215 -1.23  -0.740 
#>  8  0.397 -1.24    0.0507  -0.202   0.559 -1.10   0.132 
#>  9  0.833  0.0126  1.30     0.438   0.482 -0.294  1.13  
#> 10 -0.388  0.296  -1.44     0.833  -1.05  -0.287 -1.78