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First page of Thinking About Item Response Theory from a Logistic Regression Perspective<subtitle>A Focus on Polytomous Models</subtitle>

The purpose of this chapter is to describe the conceptual bridge between item response theory (IRT) and logistic regression (LogR) by describing the essential similarities and differences between these two statistical frameworks. In so doing, we foster knowledge translation from psychometrics to those disciplines extensively using LogR (e.g., sociology, health care, and epidemiology) hence increasing the use of IRT. Therefore, the goal of this chapter is to advance the use of item response theory in real data analyses settings. Furthermore, it becomes apparent early on in this chapter that IRT is a special case of LogR, hence one can not only use LogR as a perspective to describe IRT to novices but also as a way of IRT specialists gaining insight into complex models such as polytomous IRT and their assumptions.

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