eta {ACTCD} R Documentation

## 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.

alpha

### Examples

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


[Package ACTCD version 1.2-0 Index]