Description Usage Arguments Details Value Author(s) References See Also Examples
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.
1  as.poly.mod(n, model = "drm", items = NULL)

n 
total number of items 
model 
character vector identifying the IRT models used to estimate
the item parameters. The only acceptable models are

items 
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 drm
), only n
and model
need to be specified.
The IRT models associated with the codes:
drm
:dichotomous response models (includes the 1PL, 2PL, 3PL, M1PL, M2PL, and M3PL)
gpcm
:partial credit model, generalized partial credit model, multidimensional partial credit model, and multidimensional generalized partial credit model
grm
:graded response model and multidimensional graded response model
mcm
:multiplechoice model and multidimensional multiplechoice model
nrm
:nominal response model and multidimensional nominal response model
Returns an object of class poly.mod
Jonathan P. Weeks [email protected]
Weeks, J. P. (2010) plink: An R package for linking mixedformat tests using IRTbased methods. Journal of Statistical Software, 35(12), 1–33. URL http://www.jstatsoft.org/v35/i12/
1 2 3 4 5 6 7 8 9 10 11 12  # 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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