retention.rate

This function computes the proportion of correctly specified q-entries
in a provisional Q-matrix that remain correctly specified after a Q-matrix refinement
procedure is applied. This function is used only when the true Q-matrix is known.

Statistical tools for analyzing cognitive diagnosis (CD) data collected from small settings using the nonparametric classification (NPCD) framework. The core methods of the NPCD framework includes the nonparametric classification (NPC) method developed by Chiu and Douglas (2013) <DOI:10.1007/s00357-013-9132-9> and the general NPC (GNPC) method developed by Chiu, Sun, and Bian (2018) <DOI:10.1007/s11336-017-9595-4> and Chiu and Köhn (2019) <DOI:10.1007/s11336-019-09660-x>. An extension of the NPCD framework included in the package is the nonparametric method for multiple-choice items (MC-NPC) developed by Wang, Chiu, and Koehn (2023) <DOI:10.3102/10769986221133088>. Functions associated with various extensions concerning the evaluation, validation, and feasibility of the CD analysis are also provided. These topics include the completeness of Q-matrix, Q-matrix refinement method, as well as Q-matrix estimation.

Weixuan Xiao

NPCDTools

The Nonparametric Classification Methods for Cognitive Diagnosis

Chia-Yi Chiu

Xiran Wen

Yu Wang

retention.rate function

<dl><dt>ref.Q</dt>
<dd>the \(J \times K\) binary Q-matrix obtained from applying a refinement procedure.</dd>
<dt>mis.Q</dt>
<dd>A \(J \times K\) binary provisional Q-matrix.</dd>
<dt>true.Q</dt>
<dd>The \(J \times K\) binary true Q-matrix.</dd></dl>

Arguments

Retention rate of a Q-matrix refinement method — retention.rate

<dl>

<dt>ref.Q</dt>
<dd>the \(J \times K\) binary Q-matrix obtained from applying a refinement procedure.</dd>


<dt>mis.Q</dt>
<dd>A \(J \times K\) binary provisional Q-matrix.</dd>


<dt>true.Q</dt>
<dd>The \(J \times K\) binary true Q-matrix.</dd>

</dl>

retention.rate: Retention rate of a Q-matrix refinement method

Description

Usage

Value

Arguments