A Review of Handbook of Item Response Theory: Vol. 1

Abstract

The Handbook of Item Response Theory is an extensive three-volume collection with contributions from leading researchers in the field. This review focuses on Volume 1 (Models). Aside from the Introduction, each of the 33 chapters provides a self-contained presentation of an item response theory (IRT) modeling framework. The chapters share a common notation as well as a uniform organization (Introduction, Model Presentation, Parameter Estimation, Goodness of Fit, an Empirical Example, and a Discussion). Many chapters are leador singleauthored by original developers of the research, and in all cases, the lead authors are highly regarded as experts in the field. The Volume is organized into eight sections, each containing between two and seven chapters focused on types of data—dichotomous responses, polytomous responses, response times—or on types of models—multidimensional, nonparametric, nonmonotone, hierarchical and multilevel as well as generalized modeling approaches that include but are not limited to IRT applications. The coverage of models for polytomous data is especially strong, with seven chapters devoted to this topic. In other areas, the coverage is already appearing somewhat thin in light of recent research trends. For example, a large amount of work has been devoted to the analysis of response times since the publication of the Volume. The three chapters in the Volume provide the foundations of this more recent research, focusing the early work of Rasch, approaches based on cognitive models of decision making, and models for lognormal response times; the latter is extended to the joint modeling of responses and response times in a separate chapter. Generalized modeling approaches is another area that, in retrospect, could have received more thorough coverage of topics such as Bayesian IRT, psychometric applications of networks and graphs, or approaches based on machine learning. There is only one chapter addressing models with categorical latent variables. Despite the inevitable nit-picking about specific omissions, the Handbook certainly provides a thorough characterization of the breadth of active research on statistical models used in the IRT literature. Journal of Educational and Behavioral Statistics 2021, Vol. 46, No. 4, pp. 519–522 DOI: 10.3102/1076998620978551 Article reuse guidelines: sagepub.com/journals-permissions © 2020 AERA. http://jebs.aera.net