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Growth Modeling in a Diagnostic Classification Model (DCM) Framework–A Multivariate Longitudinal Diagnostic Classification Model [PDF]

Frontiers in Psychology, 2020
A multivariate longitudinal DCM is developed that is the composite of two components, the log-linear cognitive diagnostic model (LCDM) as the measurement model component that evaluates the mastery status of attributes at each measurement occasion, and a ...
Qianqian Pan, Lu Qin, Neal Kingston
doaj +8 more sources

Examining Parameter Invariance in a General Diagnostic Classification Model [PDF]

Frontiers in Psychology, 2020
The present study aimed at investigating invariance of a diagnostic classification model (DCM) for reading comprehension across gender. In contrast to models with continuous traits, diagnostic classification models inform mastery of a finite set of ...
Hamdollah Ravand, Purya Baghaei, Philip Doebler +2 more
doaj +7 more sources

Integrating a Statistical Topic Model and a Diagnostic Classification Model for Analyzing Items in a Mixed Format Assessment [PDF]

Frontiers in Psychology, 2021
Selected response items and constructed response (CR) items are often found in the same test. Conventional psychometric models for these two types of items typically focus on using the scores for correctness of the responses.
Hye-Jeong Choi +4 more
doaj +4 more sources

A Testlet Diagnostic Classification Model with Attribute Hierarchies. [PDF]

Appl Psychol Meas, 2023
In this article, a testlet hierarchical diagnostic classification model (TH-DCM) was introduced to take both attribute hierarchies and item bundles into account. The expectation-maximization algorithm with an analytic dimension reduction technique was used for parameter estimation.
Ma W, Wang C, Xiao J.
europepmc +4 more sources

Relating the One-Parameter Logistic Diagnostic Classification Model to the Rasch Model and One-Parameter Logistic Mixed, Partial, and Probabilistic Membership Diagnostic Classification Models

Foundations, 2023
Diagnostic classification models (DCMs) are statistical models with discrete latent variables (so-called skills) to analyze multiple binary variables (i.e., items).
Alexander Robitzsch
doaj +3 more sources

Development of a diagnostic classification model for lateral cephalograms based on multitask learning [PDF]

BMC Oral Health
Objectives This study aimed to develop a cephalometric classification method based on multitask learning for eight diagnostic classifications. Methods This study was retrospective.
Qiao Chang +7 more
doaj +2 more sources

Test-level and Item-level Model Fit Comparison of General vs. Specific Diagnostic Classification Models: A Case of True DCM

Language Testing in Asia, 2021
The current study compared the model fit indices, skill mastery probabilities, and classification accuracy of six Diagnostic Classification Models (DCMs): a general model (G-DINA) against five specific models (LLM, RRUM, ACDM, DINA, and DINO).
Mahdieh Shafipoor, Hamdollah Ravand, Parviz Maftoon +2 more
doaj +2 more sources

Corrigendum: Integrating a Statistical Topic Model and a Diagnostic Classification Model for Analyzing Items in a Mixed Format Assessment [PDF]

Frontiers in Psychology, 2021
Hye-Jeong Choi +4 more
doaj +2 more sources

Diagnostic Classification Model for Forced-Choice Items and Noncognitive Tests. [PDF]

Educ Psychol Meas, 2023
Huang HY.
europepmc +2 more sources

Automated extraction of speech and turn-taking parameters in autism allows for diagnostic classification using a multivariable prediction model

Frontiers in Psychiatry, 2023
Autism spectrum disorder (ASD) is diagnosed on the basis of speech and communication differences, amongst other symptoms. Since conversations are essential for building connections with others, it is important to understand the exact nature of ...
I. S. Plank +6 more
doaj +3 more sources

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