Several decades of psychometric research have led to the development of sophisticated models for multidimensional test data, and in recent years, multidimensional item response theory (MIRT) has become a burgeoning topic in psychological and educational measurement. Considered a cutting-edge statistical technique, the methodology underlying MIRT can be complex, and therefore doesn’t receive much attention in introductory IRT courses. However author Wes Bonifay shows how MIRT can be understood and applied by anyone with a firm grounding in unidimensional IRT modeling. His volume includes practical examples and illustrations, along with numerous figures and diagrams. Multidimensional Item Response Theory includes snippets of R code interspersed throughout the text (with the complete R code included on an accompanying website) to guide readers in exploring MIRT models, estimating the model parameters, generating plots, and implementing the various procedures and applications discussed throughout the book.

MIRT Applications

MIRT is a thriving area of methodological research—quantitative researchers and statisticians are continually developing new multidimensional models, model evaluation techniques, estimation methods, and other technical innovations. In this final chapter, we focus instead on a handful of the many novel, creative, and interesting MIRT applications that have been developed in recent years. Several of the MIRT applications that follow (e.g., linking and equating, differential item functioning, computerized adaptive testing) are extensions of well-established UIRT methods, while others (e.g., longitudinal MIRT, multilevel MIRT) have arisen as a direct result of the statistical advantages and sophistication of MIRT modeling.

Linking and Equating

Suppose we have two students, Tyrone and Martha, and we wish to compare their geographic knowledge. Unfortunately, these two students have responded to different ...

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