irt.prob-class function

Class "irt.prob"

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. class

Objects from the Class

Objects can be created by calls of the form new("irt.prob", ...), but this is not encouraged. Use one of the functions drm, gpcm, grm, mcm, nrm, or mixed instead.

Slots

• prob:: 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)
• info:: data.frame of item information
• p.cat:: vector identifying the number of categories for each item for which probabilities were computed
• mod.lab:: character vector of labels for the model(s).
• dimensions:: numeric value identifying the number of modeled dimensions
• D:: numeric vector identifying scaling constants for drm, grm, and gpcm
• pars:: list of the item parameters used to compute the probabilities
• model:: character vector identifying all the models used to compute the probabilities in prob. The only acceptable models are drm, gpcm, grm, mcm, and nrm (see class poly.mod for more information).
• items:: list with the same length as model, where each element identifies the items associated with the model(s) specified in model.

Extends

Class poly.mod, directly.

Class list.poly, by class poly.mod, distance 2.

Author(s)

Jonathan P. Weeks weeksjp@gmail.com

See Also

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

irt.pars