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| Main Authors: | , , , , |
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| Format: | Recurso educativo Open Access |
| Language: | en |
| Published: |
2019
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| Subjects: | |
| Online Access: | https://eric.ed.gov/?id=EJ1209295 |
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Table of Contents:
- Digital Module 04: Diagnostic Measurement: Modeling Checklists for Practitioners https://ncme.elevate.commpartners.com Carragher, Natacha Templin, Jonathan Jones, Phillip Shulruf, Boaz Velan, Gary Measurement Classification Models Check Lists Quality Control Data Analysis In this ITEMS module, we provide a didactic overview of the specification, estimation, evaluation, and interpretation steps for diagnostic measurement/classification models (DCMs), which are a promising psychometric modeling approach. These models can provide detailed skill- or attribute-specific feedback to respondents along multiple latent dimensions and hold theoretical and practical appeal for a variety of fields. We use a current unified modeling framework--the log-linear cognitive diagnosis model (LCDM)--as well as a series of quality-control checklists for data analysts and scientific users to review the foundational concepts, practical steps, and interpretational principles for these models. We demonstrate how the models and checklists can be applied in real-life data-analysis contexts. A library of macros and supporting files for Excel, SAS, and Mplus are provided along with video tutorials for key practices.