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Gleaning Information for Cognitive Operations from Don't Know Responses in Cognitive and Noncognitive Assessments
Edward H Ip1,2, Michelle F Magee3,4, Gretchen A Youssef3
1a Department of Biostatistical Sciences, Wake Forest School of Medicine.
Multivariate Behavioral Research
|November 2, 2018
Summary
This study introduces a new method to analyze "Don't Know" (DK) responses in tests. This approach reveals valuable insights into cognitive operations and latent traits, treating DK as a valid response.
Area of Science:
- Psychometrics
- Cognitive Science
- Survey Methodology
Background:
- Don't Know (DK) responses are often overlooked in psychometric analyses.
- Existing methods for modeling DK responses are limited.
- DK responses can contain valuable information about cognitive processes and latent traits.
Purpose of the Study:
- To propose and evaluate the Linear Logistic Test Model (LLTM) for analyzing tests with DK responses.
- To demonstrate how DK responses can inform latent construct measurement and cognitive operations.
- To validate the LLTM through simulations and real-world case studies.
Main Methods:
- Application of the Linear Logistic Test Model (LLTM) to data including DK responses.
- Assumption that DK responses are valid and contain informative data.
- Implementation of LLTM using a recoding scheme compatible with standard statistical software (e.g., PROC GLIMMIX).
Main Results:
- The LLTM can successfully delineate the impacts of cognitive operations when DK responses are included.
- Simulations demonstrated good parameter recovery for the LLTM.
- Case studies illustrated the practical application of the LLTM in health belief and diabetes knowledge assessments.
Conclusions:
- The LLTM offers a viable psychometric approach to leverage information from DK responses.
- Treating DK responses as valid enhances the understanding of cognitive processes and latent constructs.
- The proposed method provides a practical tool for researchers analyzing data with DK responses.
Keywords:
Item response theorydiabetes knowledgeitem attributelinear logistic test modelperson covariateMore Related Videos
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