Creates simulated data from structural equation models with standardized loading.
Sometimes you have a structural model with standardized path
coefficients, structural coefficients, and correlations, but you do not
know the error and disturbance variances. The purpose of simstandard
is to calculate these variances and then simulate multivariate normal
data based on your model.
You can install simstandard from github with:
# install.packages("devtools")devtools::install_github("wjschne/simstandard")
The simstandard package uses lavaan
syntax to specify models.
library(simstandard)model <- "A =~ 0.5 * A1 + 0.8 * A2B =~ 0.6 * B1 + 0.7 * B2B ~ 0.8 * AC ~~ 0.5 * A"data <- sim_standardized(m = model, n = 500)knitr::kable(head(data), digits = 2)
| A1 | A2 | B1 | B2 | C | A | B | e_A1 | e_A2 | e_B1 | e_B2 | d_B |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.05 | -1.18 | -1.00 | 1.02 | -0.12 | 0.02 | -0.22 | 0.04 | -1.19 | -0.87 | 1.17 | -0.23 |
| -0.56 | 0.07 | 0.09 | -0.11 | 0.38 | -0.69 | -0.68 | -0.22 | 0.63 | 0.50 | 0.36 | -0.13 |
| -1.05 | 0.67 | -1.13 | 0.17 | -0.02 | 0.08 | -0.15 | -1.09 | 0.61 | -1.04 | 0.27 | -0.21 |
| -1.40 | -0.95 | 0.67 | -0.32 | -0.21 | 0.34 | -0.32 | -1.57 | -1.23 | 0.86 | -0.10 | -0.60 |
| -0.38 | -1.95 | -2.62 | -0.67 | -1.20 | -1.93 | -1.04 | 0.58 | -0.41 | -2.00 | 0.06 | 0.50 |
| 0.59 | -0.04 | -0.86 | 0.97 | 2.10 | 0.66 | 0.91 | 0.26 | -0.57 | -1.41 | 0.33 | 0.38 |
See more in the tutorial for this package.