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Rasch Model

The Rasch model is a psychometric model used in the social sciences to analyze categorical response data, usually collected using a content knowledge test or attitudinal questionnaire, in order to assess the extent to which a set of persons has a certain level of an attribute of interest (e.g., mathematical proficiency or level of anxiety) and the extent to which a positive answer to the questions or statements demands a certain level of that attribute (e.g., difficulty of a mathematical question or level of anxiety required in order to agree or endorse a statement). Originally developed in the 1950s by Danish mathematician Georg Rasch for the analysis of dichotomous responses to intelligence tests, the Rasch model in its most basic form states that the probability that a person can correctly answer a test question—or that he or she endorses a given statement—can be modeled as a function of the difference between an effect associated with the person (e.g., a student’s mathematical proficiency or potentially any person property) and a question effect (e.g., the item difficulty or level of agreement demanded by a statement), such that both effects are in the same scale and

Probability of personpcorrectly answering itemi=f(Personpproficiency  itemidifficulty).

In other words, the Rasch model considers the performance of a person on a question to be a product of the trade-off between a person effect (oftentimes interpreted as the level of person proficiency) and an item effect (commonly interpreted as the difficulty of the item). The Rasch model is widely applied in the social sciences, particularly in the context of psychometric analysis of educational testing, where it is often considered to be a special case within item response theory (IRT), and, more generally, as a special case of a generalized linear model (GLM) in statistics. Although it can formally be understood as a special case within item response theory or GLMs, the Rasch model was developed by Rasch under a specific set of theoretical commitments regarding the nature of measurement in the social sciences and the requirements that a model must fulfill in order to be used for measurement, which have historically set apart the use and development of the Rasch model and its extensions from the wider psychometric and statistical literature.

Three Mathematical Formulations of the Rasch Model

In its original form, the Rasch model expresses the expected relation between a set of observed dichotomous responses and a set of unobserved person and item effects. This relation can be expressed in multiple ways, casting the relations between persons and items in alternative, but mathematically equivalent, manners. However, it is important to remember that regardless of the formulation, under the Rasch model, persons are solely characterized in terms of their proficiency and items are fully characterized in terms of their difficulty, and that different formulations simply express the relations between these parameters in alternative forms. There are at least three common ways of formulating the Rasch model: by focusing on the probability of answering correctly, the odds of answering correctly, and the log odds or logit of answering correctly. For the remainder of this entry, “answering correctly” will be used as any positive answer to an item, even if in some cases (e.g., attitude questionnaires) there is no “correct” response.

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