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.

Unidimensional Item Response Theory

This chapter a brief review of unidimensional aimed at readers who are already familiar with the topic. The goal of this chapter is to refresh your memory of unidimensional IRT models and methods in preparation for the following chapters on MIRT. Each of the sections in this chapter includes only the essential details, with limited technical discussion. References for further reading are included throughout, though most IRT texts (e.g., de Ayala, 2009; Embretson & Reise, 2000; Thissen & Wainer, 2001) offer in-depth coverage of the topics discussed in the following.

What Is a Latent Trait?

IRT is a statistical framework for the measurement of psychological variables, which are commonly referred to as constructs, attributes, or traits. Examples of such traits include intelligence, ...

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