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

By Andre A. Rupp, Jonathan Templin. 2008

242 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/1dc1106c94760689789f920fbf9d7399e213bff0

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In Management Science and Operations Research

In Statistics and Probability

Citations in the corpus

Statistical Refinement of the Q-Matrix in Cognitive Diagnosis (2013, background): “It is widely recognized (e.g., de la Torre, 2008; de la Torre & Chiu, 2010; Rupp & Templin, 2008) that a misspecified Q-matrix can negatively affect the estimation of the model parameters, which may then result in the misclassification of examinees, but little research into methods for detecting…”
On the Estimation of Standard Errors in Cognitive Diagnosis Models (2018, background): “However, in practice (especially when retrofitting CDMs to existing data), the Q-matrix may be unknown or misspecified, which can affect parameter estimation and classification accuracy (de la Torre, 2008; Rupp & Templin, 2007).”
On the Analysis of Fraction Subtraction Data: The DINA Model, Classification, Latent Class Sizes, and the Q-Matrix (2011, methodology): “Note that problems such as the above can be avoided if, for each of the skills, there are items that load solely on that skill (given that CDMs are a type of discrete factor model); this type of Q-matrix has been used in some simulations (e.g., Rupp & Templin, 2008b).”
Unique Characteristics of Diagnostic Classification Models: A Comprehensive Review of the Current State-of-the-Art (2008, background): “Rupp and Templin (2008) and Rupp (2008b), following other research on DCM model robustness, investigated the sensitivity of item parameters and classification accuracy in the DINA model to misspecification in the Q-matrix, which was further formalized into an item-fit index by de la Torre (2007).”
Diagnosing Teachers’ Understandings of Rational Numbers: Building a Multidimensional Test Within the Diagnostic Classification Framework (2014, background): “DCM classification accuracy hinges on the correct alignment of items with attributes, as Q-matrix misspecifications result in more frequent misclassification (Rupp & Templin, 2008).”