An empirical Q‐matrix validation method for the sequential generalized DINA model

As a core component of most cognitive diagnosis models, the Q‐matrix, or item and attribute association matrix, is typically developed by domain experts, and tends to be subjective. It is critical to validate the Q‐matrix empirically because a misspecified Q‐matrix could result in erroneous attribut...

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Vydáno v:	British journal of mathematical & statistical psychology Ročník 73; číslo 1; s. 142 - 163
Hlavní autoři:	Ma, Wenchao, Torre, Jimmy
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	England British Psychological Society 01.02.2020
Témata:	Algorithms Cognition Cognition Disorders - diagnosis cognitive diagnosis Computer Simulation discrimination index Empirical analysis G‐DINA Humans Mathematical analysis Matrix methods Models, Statistical Psychometrics - methods Q‐matrix validation sequential G‐DINA stepwise Task Performance and Analysis Trends in International Mathematics and Science Study Wald test sequential G-DINA Wald test cognitive diagnosis stepwise Trends in International Mathematics and Science Study Q-matrix validation G-DINA discrimination index
ISSN:	0007-1102, 2044-8317, 2044-8317
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Shrnutí:	As a core component of most cognitive diagnosis models, the Q‐matrix, or item and attribute association matrix, is typically developed by domain experts, and tends to be subjective. It is critical to validate the Q‐matrix empirically because a misspecified Q‐matrix could result in erroneous attribute estimation. Most existing Q‐matrix validation procedures are developed for dichotomous responses. However, in this paper, we propose a method to empirically detect and correct the misspecifications in the Q‐matrix for graded response data based on the sequential generalized deterministic inputs, noisy ‘and’ gate (G‐DINA) model. The proposed Q‐matrix validation procedure is implemented in a stepwise manner based on the Wald test and an effect size measure. The feasibility of the proposed method is examined using simulation studies. Also, a set of data from the Trends in International Mathematics and Science Study (TIMSS) 2011 mathematics assessment is analysed for illustration.
Bibliografie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 ObjectType-Undefined-3
ISSN:	0007-1102 2044-8317 2044-8317
DOI:	10.1111/bmsp.12156