model.MGGUM: Compute MGGUM Category Response Probabilities

In ForceChoice: Forced-Choice Modeling Based on Item Response Theory and Cognitive Diagnostic Models

Compute MGGUM Category Response Probabilities

Description

Compute MGGUM Category Response Probabilities

Usage

model.MGGUM(theta, par)

Arguments

theta	N \times D matrix of latent trait values.
par	I \times (2D + \max K_i) parameter matrix with columns a1..aD, delta1..deltaD, tau0, tau1, .... Missing category columns for shorter items should be NA; tau0 is fixed at 0.

Value

An N \times \sum_i K_i matrix of stacked category probabilities. The implementation uses r_{ij} = [\sum_d a_{id}^2(\theta_{jd}-\delta_{id})^2]^{1/2} and P(Y_{ij}=k) \propto \exp\{k r_{ij}-\psi_{ik}\} + \exp\{(2K_i-1-k)r_{ij}-\psi_{ik}\}.

ForceChoice documentation built on Sept. 13, 2026, 1:06 a.m.