```
# NOT RUN {
## Generate data for a simple sample with two variables without selection:
simulate_psych(n = 1000, rho_mat = matrix(c(1, .5, .5, 1), 2, 2), sigma_vec = c(1, 1),
rel_vec = c(.8, .8), var_names = c("Y", "X"))
## Generate data for a simple sample with two variables with selection:
simulate_psych(n = 1000, rho_mat = matrix(c(1, .5, .5, 1), 2, 2), sigma_vec = c(1, 1),
rel_vec = c(.8, .8), sr_vec = c(1, .5), var_names = c("Y", "X"))
## Generate data for samples with five variables, of which subsets are used to form composites:
rho_mat <- matrix(.5, 5, 5)
diag(rho_mat) <- 1
simulate_psych(n = 1000, rho_mat = rho_mat,
rel_vec = rep(.8, 5), sr_vec = c(1, 1, 1, 1, .5),
wt_mat = cbind(c(0, 0, 0, .3, 1), c(1, .3, 0, 0, 0)), sr_composites = c(.7, .5))
## Generate data for similar scenario as above, but with scales consisting of 1-5 items:
rho_mat <- matrix(.5, 5, 5)
diag(rho_mat) <- 1
simulate_psych(n = 1000, rho_mat = rho_mat,
rel_vec = rep(.8, 5), sr_vec = c(1, 1, 1, 1, .5),
k_items_vec = 1:5,
wt_mat = cbind(c(0, 0, 0, .3, 1), c(1, .3, 0, 0, 0)), sr_composites = c(.7, .5))
# }
```

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