The Effects of Q-Matrix Misspecification on Parameter Estimates and Classification Accuracy in the DINA Model  

Oleh:

Rupp, André A. ; Templin, Jonathan

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Educational and Psychological Measurement vol. 68 no. 01 (Feb. 2008), page 78-96.
Topik: deterministic-input; noisy ‘‘and’’ gate model; DINA model; Q-matrix; simulation study
Fulltext: 78.pdf (246.14KB)

Isi artikel

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 itemspecific 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.

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