A Multidimensional Item Response Modeling Approach for Improving Subscale Proficiency Estimation and Classification

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Unique Characteristics of Diagnostic Classification Models: A Comprehensive Review of the Current State-of-the-Art (2008, background): “Just like with other multidimensional models, larger numbers of skills are more challenging to separate empirically than smaller number of skills ( Haberman, 2008 ; Sinhary, Haberman, & Puhan, 2007; Yao & Boughton, 2007 ; Rupp, 2008a ).”
Reporting of Subscores Using Multidimensional Item Response Theory (2010, methodology): “For example, the MCMC algorithm employed in de la Torre and Patz (2005 )o r Yao and Boughton (2007) is more computationally intensive than is currently practical given the time constraints of many testing programs.”
Simultaneous Estimation of Overall and Domain Abilities: A Higher-Order IRT Model Approach (2009, methodology): “Similarly, using information on other subtests, de la Torre and Patz (2005), Wang, Chen, and Cheng (2004), and Yao and Boughton (2007) used a multidimensional IRT framework to obtain more precise ability estimates for test domains or subsections.”