Properties and performance of the one-parameter log-linear cognitive diagnosis model
Bibliographic Data
| ID | 22166403 |
|---|---|
| Authors | Lientje Maas (0000-0001-5334-1755, Utrecht University, corresponding author), Matthew J Madison (0000-0002-2944-7442, University of Georgia), Matthieu Brinkhuis (0000-0003-1054-6683, Utrecht University), Matthieu J S Brinkhuis |
| Year | 2024 |
| Volume | 9 |
| Publication date | 2024-01-23 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Education (JOURNAL) |
| Journal identifiers | ISSN: 2504-284X • E-ISSN: 2504-284X |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/feduc.2024.1287279 |
| OpenAlex | W4391143818 |
| Language | EN |
| References cited | 35 |
Diagnostic classification models (DCMs) are psychometric models that yield probabilistic classifications of respondents according to a set of discrete latent variables. The current study examines the recently introduced one-parameter log-linear cognitive diagnosis model (1-PLCDM), which has increased interpretability compared with general DCMs due to useful measurement properties like sum score sufficiency and invariance properties. We demonstrate its equivalence with the Latent Class/Rasch Model and discuss interpretational consequences. The model is further examined in a DCM framework. We demonstrate the sum score sufficiency property and we derive an expression for the cut score for mastery classification. It is shown by means of a simulation study that the 1-PLCDM is fairly robust to model constraint violations in terms of classification accuracy and reliability. This robustness in combination with useful measurement properties and ease of interpretation can make the model attractive for stakeholders to apply in various assessment settings
Cognition · Linear model · Log-linear model · Machine learning · Statistics · Bayesian Modeling and Causal Inference · Computer Science · Decision-Making and Behavioral Economics · Mathematics · Multi-Criteria Decision Making · Psychology · Applied Mathematics
Invariant Measurement
Item Response Theory
The Generalized Dina Model Framework
Diagnostic Classification Models for Actionable Feedback in Education
The Effects of Q-Matrix Design on Classification Accuracy in the Log-Linear Cognitive Diagnosis Model
Assessing Approximate Fit in Categorical Data Analysis
Adaptive Measurement and Assessment
The problem of equivalent models in applications of covariance structure analysis
| Citation velocity | historical |
|---|---|
| Highly cited | No |