eta: Ideal Response Patterns for all possible attribute profiles

In ACTCD: Asymptotic Classification Theory for Cognitive Diagnosis

Ideal Response Patterns for all possible attribute profiles

Description

This function is used to calculate ideal response patterns for all possible attribute profiles based on the DINA model (Junker & Sijtsma, 2001) or conjunctive-type cognitive diagnostic models.

Usage

eta(K, J, Q)

Arguments

K	The number of attributes.
J	The number of items.
Q	A required J \times K binary item-by-attribute association matrix (Q-matrix), where K is the number of attributes. The j^{th} row of the matrix is an indicator vector, 1 indicating attributes are required and 0 indicating attributes are not required to master item j.

Value

A 2^K \times J binary matrix will be returned. Each row of ideal response patterns is corresponding to each of the 2^K possible attribute patterns, which can be obtained from alpha.

References

Junker, B., & Sijtsma, K. (2001). Cognitive Assessment Models with Few Assumptions, and Connections with Nonparametric Item Response Theory. Applied Psychological Measurement, 25(3), 258-272.

See Also

alpha

Examples

# Generating ideal response patterns
data(sim.Q)
K <- ncol(sim.Q)
J <- nrow(sim.Q)
IRP <- eta(K, J, sim.Q) 

ACTCD documentation built on Nov. 10, 2023, 1:12 a.m.