The formal S4 class for irt.prob. This class contains the expected probabilities of responding in a given category for a set of items and theta values under the specified IRT models. The class also includes characteristics of the items.
Objects can be created by calls of the form
new("irt.prob", ...), but this is
not encouraged. Use one of the functions
data.frame of item probabilities with n rows and j+m columns for n theta values and j items (the first m column contains theta values for m dimensions)
data.frame of item information
vector identifying the number of categories for each item for which probabilities were computed
character vector of labels for the model(s).
numeric value identifying the number of modeled dimensions
numeric vector identifying scaling constants for
list of the item parameters used to compute the probabilities
character vector identifying all the models used to compute the
prob. The only acceptable models are
nrm (see class
poly.mod for more
list with the same length as
model, where each element
identifies the items associated with the model(s) specified in
list.poly, by class
poly.mod, distance 2.
Jonathan P. Weeks email@example.com
These models provide information on both unidimensional and multidimensional formulations
drm: for dichotomous response models (1PL, 2PL, and 3PL)
gpcm: for the partial credit/generalized partial credit model
grm: for the graded response model
mcm: for the multiple-choice model
nrm: for the nominal response model
mixed: for mixed-format items
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