Construct valdity relates to whether a particular psychometric assessment...
Lead consultant at Test Partnership, Ben Schwencke, explains what is item response theory.
Item Response Theory (IRT) is a modern psychometric test theory that is increasingly replacing the classical test theory (CTT) as the underlying theoretical framework for psychometric testing. IRT is a more complex theory than CTT, and it is particularly useful when creating item-banked assessments. IRT's main objective is to ensure reliability, precision, and accuracy of psychometric test scores by minimizing measurement error.
IRT posits that several factors influence a person’s observed score, including the person's true score, question difficulty, item discrimination, and guessing. Unlike CTT, IRT allows for the estimation of item parameters such as difficulty and discrimination, which allows for the creation of item-banked assessments. This means that IRT can account for differences in question difficulty, item discrimination, and guessing, all of which require parametrization in item banked assessments.
In IRT, test scores are estimated by taking into account not only the test-taker's true score but also the item characteristics, such as difficulty and discrimination. This approach allows for the creation of multiple forms of a test that can be used to reduce the impact of test-taking strategies on test scores. Additionally, IRT allows for the estimation of person parameters such as ability or latent trait scores, which can be used to create more accurate and fair test scores.
IRT is more complex than CTT, however, it is considered a more accurate and powerful psychometric tool because it can account for the complexity of item-banking and it can estimate person parameters. It is also useful when creating adaptive tests, which are tailored to the test-taker's ability level, by adjusting the difficulty of the items they are presented with. This increases the reliability of the assessment considerably, allowing psychometricians to shorten the assessment while simultaneously retaining or increasing the precision of measurement.