gpcm.rc: IRT Derived Predicted Conditional Number Correct Score...

In classify: Classification Accuracy and Consistency under IRT models.

Description

Obtains the predicted number-correct score distribution from parameters estimated under the Generalised Partial Credit Model.

Usage

  gpcm.rc(beta=NULL,theta=NULL,cats=NULL,alpha=NULL)

Arguments

beta	Item threshold parameters. These should be a matrix, with rows for items and columns for categories. Following Muraki, the first column should be zero.
theta	Theta parameters
cats	Vector of item categories. A dichotomous item is specified as two categories.
alpha	Discrimination parameters. If none are specified the model will default to the Partial Credit Model.

Details

The beta parameters are defined as the intersection points of adjacent category information functions. There should be the same number of beta parameters as categories, with the first column, following Muraki, specified as zero.

Value

Vector of probabilities of achieving any item score

Examples

beta <- matrix(c(0,-1.586,-3.798),nrow=1,ncol=3)
theta <- 0.674
cats <- 3
alpha <- 1
gpcm.rc(beta,theta,cats,alpha)

classify documentation built on May 29, 2017, 7:49 p.m.