probgpcm: calculates item response probabilities according to GPCM
In lordif: Logistic Ordinal Regression Differential Item Functioning using IRT

Description Usage Arguments Details Value Author(s) References See Also Examples

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

1	probgpcm(theta, a, cb)

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

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

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

Seung W. Choi <choi.phd@gmail.com>

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

calcprob, probgrm

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

Loading required package: mirt
Loading required package: stats4
Loading required package: lattice
Loading required package: rms
Loading required package: Hmisc
Loading required package: survival
Loading required package: Formula
Loading required package: ggplot2

Attaching package: 'Hmisc'

The following objects are masked from 'package:base':

    format.pval, units

Loading required package: SparseM

Attaching package: 'SparseM'

The following object is masked from 'package:base':

    backsolve

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