simstandard (version 0.3.0)

sim_standardized: Generates simulated data with standardized parameters.

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`

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

# NOT RUN {
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)
# }