Item response models may refer either to item-response theory (IRT) or Rasch models. Although not synonymous, both forms of model are measurement or psychometric methods that can be applied to a wide range of data, including that derived from patient-reported outcome (PRO) measures. A particular strength of these models is that their focus is (as the name implies) on the item-level rather than test-level (as seen in traditional or classical test theory). This has a number of benefits, the two most important of which are 1) researchers can identify (and potentially remove or amend) poorly performing items, for example those that are not relevant to the target audience, and 2) item banks (drawn from many PRO measures) together with computer-adaptive testing (CAT) may enable the creation of shorter, more relevant, but equally accurate tests.


How to cite: Item Response Models [online]. (2016). York; York Health Economics Consortium; 2016.


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