Journal article
The effects of Q-Matrix misspecification on parameter estimates and classification accuracy in the DINA model
Educational and psychological measurement, Vol.68(1), pp.78-96
02/01/2008
DOI: 10.1177/0013164407301545
Abstract
This article reports a study that investigated the effects of Q-matrix misspecifications on parameter estimates and misclassification rates for the deterministic-input, noisy '' and '' gate (DINA) model, which is a restricted latent class model for multiple classifications of respondents that can be useful for cognitively motivated diagnostic assessment. In this study, a Q-matrix for an assessment mapping all 15 possible attribute patterns based on four independent attributes was misspecified by changing one '' 0 '' or '' 1 '' for each item. This was done in a way that ensured that certain attribute combinations were completely deleted from the Q-matrix, and certain incorrect dependency relationships between attributes were represented. Results showed clear effects that included an item-specific overestimation of slipping parameters when attributes were deleted from the Q-matrix, an item-specific overestimation of guessing parameters when attributes were added to the Q-matrix, and high misclassification rates for attribute classes that contained attribute combinations that were deleted from the Q-matrix.
Details
- Title: Subtitle
- The effects of Q-Matrix misspecification on parameter estimates and classification accuracy in the DINA model
- Creators
- Andre A. Rupp - Humboldt-Universität zu BerlinJonathan Templin - University of Kansas
- Resource Type
- Journal article
- Publication Details
- Educational and psychological measurement, Vol.68(1), pp.78-96
- Publisher
- Sage
- DOI
- 10.1177/0013164407301545
- ISSN
- 0013-1644
- eISSN
- 1552-3888
- Number of pages
- 19
- Language
- English
- Date published
- 02/01/2008
- Academic Unit
- Psychological and Quantitative Foundations
- Record Identifier
- 9984371085702771
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