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Item response models are a family of statistical models that describe the relationship between a person's level on an underlying latent trait, such as physical function, and the probability of a particular response to each item of a measure, taking account of item characteristics such as difficulty and discrimination. Unlike classical approaches, they treat item properties and person abilities on a common scale, enabling detailed evaluation of how each item performs, the construction of efficient and even adaptive instruments, and the equating of scores across different item sets. They are used in the sophisticated development and refinement of outcome measures and in ensuring that instruments perform consistently across populations. Their application requires substantial data and technical expertise but yields robust, well-characterised measurement.

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