A Cognitive Diagnosis Model for Cognitively Based Multiple-Choice Options

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The Generalized DINA Model Framework. (2011, methodology): “Sample size and attribute distribution are particularly salient for the G-DINA model because, as de la Torre (2009a) has shown, the stability of proportion-based parameter estimates can in part be traced to the number of observations used in estimating these parameters.”
Towards a Theory of Diagnosis in Second and Foreign Language Assessment: Insights from Professional Practice Across Diverse Fields (2015, background): “…ex post facto ‘cognitive diagnosis models’—discrete latent variable models—to tests that have not necessarily been designed with diagnosis in mind, but where performance on particular test items might be associated with strengths and weaknesses with particular ‘sub-skills’ (de la Torre 2009).”
Cognitively Diagnostic Assessments and the Cognitive Diagnosis Model Framework (2014, background): “It should also be noted that multiple-choice CDMs exist to go beyond right-or-wrong (i.e., 0/1) scoring (see de la Torre, 2009).”
Developing, Analyzing, and Using Distractors for Multiple-Choice Tests in Education: A Comprehensive Review (2017, methodology): “To make inferences about students’ attribute mastery, de la Torre (2009) modified the deterministic-input noisy “and” gate (DINA; Junker & Sijtsma, 2001) model to allow item responses to have more than two categories.”