An empirical Q‐matrix validation method for the sequential generalized DINA model. (5th February 2019)

• Record Type: Journal Article
• Authors: Ma, Wenchao; de la Torre, Jimmy
• Is Part Of: British journal of mathematical & statistical psychology. Volume 73:Part 1(2020)
• Page Start: 142
• Page End: 163
• Publication Date: 2019-02-05
• Subjects: cognitive diagnosis -- discrimination index -- G‐DINA -- Q‐matrix validation -- sequential G‐DINA -- stepwise -- Trends in International Mathematics and Science Study -- Wald test; Psychometrics -- Periodicals; Psychology -- Mathematical models -- Periodicals; Psychology -- Statistical methods -- Periodicals; 150.727
• DOI: 10.1111/bmsp.12156
• Languages: English
• ISSNs: 0007-1102

Abstract

Abstract : 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.