Description Objects from the Class Slots Extends Author(s) See Also

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 `drm`

, `gpcm`

, `grm`

, `mcm`

,
`nrm`

, or `mixed`

instead.

`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`

.

Class `poly.mod`

, directly.

Class `list.poly`

, by class `poly.mod`

, distance 2.

Jonathan P. Weeks weeksjp@gmail.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

`irt.pars`

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