This function attempts to turn the given values into a
poly.mod object that
associates each item with a specific unidimensional or multidimensional item response model.
total number of items
character vector identifying the IRT models used to estimate
the item parameters. The only acceptable models are
list identifying the item numbers from a set of parameters
that correspond to the given model in
When creating a
poly.mod object, there is no difference in the specification for
unidimensional versus multidimensional item response models. If all the items are dichotomous,
it is only necessary to specify a value for
n. If all the items correspond to a
single model (other than
model need to be specified.
The IRT models associated with the codes:
dichotomous response models (includes the 1PL, 2PL, 3PL, M1PL, M2PL, and M3PL)
partial credit model, generalized partial credit model, multidimensional partial credit model, and multidimensional generalized partial credit model
graded response model and multidimensional graded response model
multiple-choice model and multidimensional multiple-choice model
nominal response model and multidimensional nominal response model
Returns an object of class
Jonathan P. Weeks [email protected]
Weeks, J. P. (2010) plink: An R package for linking mixed-format tests using IRT-based methods. Journal of Statistical Software, 35(12), 1–33. URL http://www.jstatsoft.org/v35/i12/
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# Ten dichotomous items as.poly.mod(10) # The first ten items in the set of associated (not present here) item # parameters are dichotomous and the last five were estimated using the # generalized partial credit model as.poly.mod(15, c("drm", "gpcm"), list(1:10,11:15) ) # Ten multidimensional graded response model items # Note: This same specification would be used for a unidimensional # graded response model as.poly.mod(10, "grm")
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