ttm_est

Calibrates the TTM using score data and pre-computed topic proportions.
Uses a Variational Expectation-Maximization (VEM) approach to estimate
student ability (theta), topic penalties (lambda), and item parameters (b).

Implements the Topic Testlet Model (TTM) as described by Xiong et al. (2025) <doi:10.1111/jedm.70001>.
The package integrates Latent Dirichlet Allocation (LDA) with the Partial Credit Model to
account for local item dependence in testlets using latent topics from student
textual responses.

Jiawei Xiong

TopicTestlet

A Topic Testlet Model for Calibrating Testlet Constructed
Responses

Cheng Tang

Qidi Liu

ttm_est function

<dl><dt>scores</dt>
<dd>An N x J numeric matrix of item scores (0, 1, ...).</dd>
<dt>delta</dt>
<dd>An N x K numeric matrix of topic proportions (from ttm_lda).</dd>
<dt>max_iter</dt>
<dd>Maximum number of EM iterations.</dd>
<dt>tol</dt>
<dd>Convergence tolerance.</dd></dl>

Arguments

Fit the Topic Testlet Model (TTM) — ttm_est

<dl>

<dt>scores</dt>
<dd>An N x J numeric matrix of item scores (0, 1, ...).</dd>


<dt>delta</dt>
<dd>An N x K numeric matrix of topic proportions (from ttm_lda).</dd>


<dt>max_iter</dt>
<dd>Maximum number of EM iterations.</dd>


<dt>tol</dt>
<dd>Convergence tolerance.</dd>

</dl>

ttm_est: Fit the Topic Testlet Model (TTM)

Description

Usage

Value

Arguments