IRT stands for Item Response Theory, which is a statistical framework used in psychometrics to analyze the responses of individuals to test items or questions. It is commonly used in educational measurement and psychological assessments to evaluate and measure various attributes such as knowledge, abilities, attitudes, or personality traits.
Key concepts in IRT include item difficulty, item discrimination, and person ability. Item difficulty refers to how hard or easy an item is, while item discrimination refers to how well an item can differentiate between individuals with higher and lower abilities. Person ability represents the level of the construct being measured possessed by an individual.
IRT models use item response data to estimate parameters such as item difficulty, item discrimination, and person ability. Some commonly used IRT models include the Rasch model, the two-parameter logistic model (2PL), and the three-parameter logistic model (3PL). These models allow for precise measurement of the latent trait being assessed and provide a more accurate estimation of individual abilities compared to classical test theory.
Advantages of IRT include its ability to provide item-level information, assess item and person fit, and enable the development of calibrated item banks. It also allows for adaptive testing where the next item presented to a respondent is selected based on their response to the previous item, leading to more efficient and accurate measurement.
In summary, IRT is a powerful statistical framework used in psychometrics to analyze test responses and estimate item and person parameters. It has various applications in educational and psychological assessments, contributing to the development of reliable and valid measurement instruments.
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