sim.Q

generate a \(I\) * \(K\) Q-matrix randomly, which consisted of one-attribute q-vectors
(0.5), two-attribute q-vectors (0.25), and three-attribute q-vectors (0.25).

Provide a variety of Q-matrix validation methods for the generalized cognitive diagnosis models, including the method based on the generalized deterministic input, noisy, and gate model (G-DINA) by de la Torre (2011) <DOI:10.1007/s11336-011-9207-7> discrimination index (the GDI method) by de la Torre and Chiu (2016) <DOI:10.1007/s11336-015-9467-8>, the step-wise Wald test method (the Wald method) by Ma and de la Torre (2020) <DOI:10.1111/bmsp.12156>, the Hull method by Najera et al. (2021) <DOI:10.1111/bmsp.12228>, the multiple logistic regression‑based Q‑matrix validation method (the MLR-B method) by Tu et al. (2022) <DOI:10.3758/s13428-022-01880-x>. Different research methods during Q-matrix validating are available.

Haijiang Qin

Qval

The Q-Matrix Validation Methods Framework

Lei Guo

sim.Q function

<dl><dt>K</dt>
<dd>The number of attributes of each item.</dd>
<dt>I</dt>
<dd>The number of items.</dd></dl>

Arguments

Haijiang Qin &lt;Haijiang133@outlook.com&gt;

Author

generate a random Q-matrix — sim.Q

<dl>

<dt>K</dt>
<dd>The number of attributes of each item.</dd>


<dt>I</dt>
<dd>The number of items.</dd>

</dl>

sim.Q: generate a random Q-matrix

Description

Usage

Value

Arguments

Author

References

Examples