probgpcm: calculates item response probabilities according to GPCM

In lordif: Logistic Ordinal Regression Differential Item Functioning using IRT

calculates item response probabilities according to GPCM

Description

Calculates a matrix of item response probabilities over a grid of theta values for an item

Usage

  probgpcm(theta, a, cb)

Arguments

theta	a vector of theta values (e.g., quadrature points)
a	a slope parameter value
cb	a vector of category threshold values

Details

The Generalized Partial Credit Model (Muraki, 1992) is assumed.

Value

Returns a matrix of item response probabilities. The first dimension corresponds to the length of theta.

Author(s)

Seung W. Choi <[e-mail]>

References

Muraki, E. (1992). A generalized partial credit model: Application of an EM algorithm. Applied Psychological Measurement, 16, 159-176.

See Also

calcprob, probgrm

Examples

probgrm(seq(-4,4,.1), 1.5, c(-1.2,0.5,1.5))

lordif documentation built on April 3, 2025, 10:37 p.m.