| generateCovItems {pcFactorStan} | R Documentation |
Generate paired comparison data with random correlations between items
Description
If you need access to the correlation matrix used to generate the absolute latent scores then you will need to generate them yourself. This is not difficult. See how in the example.
Usage
generateCovItems(df, numItems, th = 0.5, name, ..., scale = 1, alpha = 1)
Arguments
df |
a data frame with pairs of vertices given in columns |
numItems |
how many items to create |
th |
a vector of thresholds |
name |
a vector of item names |
... |
Not used. Forces remaining arguments to be specified by name. |
scale |
a vector of scaling constants |
alpha |
a vector of item discriminations |
Value
The given data.frame df with additional columns for each item.
In addition, you can obtain the correlation matrix used
to generate the latent worths from attr(df, "cor") and
and latent worths from attr(df, "worth").
Response model
See cmp_probs for details.
See Also
Other item generators:
generateFactorItems(),
generateItem(),
generateSingleFactorItems()
Examples
library(mvtnorm)
df <- twoLevelGraph(letters[1:10], 100)
df <- generateCovItems(df, 3)
# generateCovItems essentially does the same thing as:
numItems <- 3
palist <- letters[1:10]
trueCor <- cov2cor(rWishart(1, numItems, diag(numItems))[,,1])
theta <- rmvnorm(length(palist), sigma=trueCor)
dimnames(theta) <- list(palist, paste0('i', 3 + 1:numItems))
df <- generateItem(df, theta)
attr(df, "cor")