sim_standardized: Generates simulated data with standardized parameters.

In simstandard: Generate Standardized Data

Description

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

Usage

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'

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.

Value

tibble with standardized data

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)

simstandard documentation built on May 8, 2021, 1:06 a.m.