```
# NOT RUN {
## Create a dataset in which constructs correlate with themselves
rxyi <- seq(.1, .5, length.out = 27)
construct_x <- rep(rep(c("X", "Y", "Z"), 3), 3)
construct_y <- c(rep("X", 9), rep("Y", 9), rep("Z", 9))
dat <- data.frame(rxyi = rxyi,
construct_x = construct_x,
construct_y = construct_y,
stringsAsFactors = FALSE)
dat <- rbind(cbind(sample_id = "Sample 1", dat),
cbind(sample_id = "Sample 2", dat),
cbind(sample_id = "Sample 3", dat))
## Identify some constructs for which intercorrelations are not
## represented in the data object:
construct_names = c("U", "V", "W")
## Specify some externally determined intercorrelations among measures:
intercor_vec <- c(W = .4, X = .1)
## Specify a generic scalar intercorrelation that can stand in for missing values:
intercor_scalar <- .5
control_intercor(rxyi = rxyi, sample_id = sample_id,
construct_x = construct_x, construct_y = construct_y,
construct_names = construct_names,
intercor_vec = intercor_vec, intercor_scalar = intercor_scalar, data = dat)
# }
```

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