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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 either install simstandard from CRAN or install the development version of simstandard from github.
You can install simstandard from CRAN by running this code:
install.packages("simstandard")To install the development version of simstandard, you need to check if the remotes packages is installed. If not, run this:
install.packages("remotes")Once you are sure you have the remotes package installed, you can install the development version of simstandard from GitHub by running this code:
remotes::install_github("wjschne/simstandard")The simstandard package uses lavaan syntax
to specify models.
library(simstandard)
model <- "
A =~ 0.5 * A1 + 0.8 * A2
B =~ 0.6 * B1 + 0.7 * B2
B ~ 0.8 * A
C ~~ 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| -1.31 | -1.03 | -0.80 | -0.97 | 1.08 | -0.11 | 0.55 | -1.26 | -0.94 | -1.13 | -1.35 | 0.63 |
| 0.38 | 1.24 | 0.64 | 0.75 | -0.73 | 0.00 | 1.20 | 0.38 | 1.24 | -0.08 | -0.08 | 1.20 |
| -0.83 | -0.55 | 2.12 | 1.21 | -0.25 | 0.12 | 1.02 | -0.88 | -0.65 | 1.51 | 0.50 | 0.93 |
| 1.13 | -0.23 | 1.51 | 1.40 | 0.92 | 0.40 | 1.31 | 0.93 | -0.55 | 0.73 | 0.48 | 0.99 |
| 0.90 | -0.62 | -0.85 | -0.28 | -0.30 | -0.19 | -0.43 | 0.99 | -0.47 | -0.60 | 0.02 | -0.28 |
| 0.05 | 0.63 | 0.90 | 1.14 | 1.03 | 0.46 | 0.76 | -0.18 | 0.26 | 0.45 | 0.61 | 0.39 |
See more in the tutorial for this package.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.