Item Response Theory

Item Response Theory (IRT) refers to a series of mathematical models that attempt to articulate the relationship between untapped properties (unobservable properties or properties) and their manifestations (i.e., perceived outcomes, responses, or performance). It establishes a link between properties of instrument items, individuals responding to those items, and untapped properties being measured are linked. IRT assumes that underlying structures (e.g., stress, knowledge, attitudes) and measured elements are organised on an unobservable continuum. Thus, its substantial purpose is to establish the individual’s place on this continuum.

Item Response Theory For Psychologists

Item Response Theory (IRT) is one of the most vibrant developments in the field of education and psychometrics. IRT consolidate a foundation for statistical methods used in environments such as test development, project analysis, equalisation, project libraries, and computer-adaptive testing. Its application also propagates to the measurement of various substantial structures in different disciplines. The success and influence of IRT over its predecessor, classical test theory, stems mainly from IRT’s focus on the individual integrants that make up the measurement. That is, on the test project itself. By modelling the outcomes at the item level rather than at the test level in classical test theory, IRT is comparatively more complex but also more succinct in giving information about test performance.

Item Response Theory Principles and Application

It is crucial to have a measurement scale to measure latent properties, but defining the scale and the intervals on the scale is a difficult task. To measure psychometric ability, a test containing a list of items is often developed. Each item helps measure some aspect of interest ability. This concept is mainly used in competitions, where respondents can write any answers they deem fit.

Questions are dichotomous, with candidates scoring 1 point for each correct answer and 0 points for each incorrect answer. In classical test theory, scores are determined by adding individual scores for each element. In IRT, the focus is on a single item rather than a series of responses to an item. Each respondent owns a portion of the underlying asset. This capacity fraction is represented by the letters theta. At any skill level, candidates are likely to answer questions correctly. This probability is represented by P(theta). Respondents with low theta values have low P(theta) values and vice versa.

Difficulty: Difficulty describes the exact work location for the item based on skill level. Hard items are for high-skilled candidates, while easy items are for low-skilled candidates.

Discrimination: Discrimination describes a program’s ability to distinguish between individuals or candidates with abilities above and below the program’s position. The steepness of the slope is proportional to the discriminant value of the curve. The steeper the curve, the better it can differentiate items. A flat curve will have a 0 discrimination factor.

Knowing these parameters, we use maximum probability estimates to calculate theta values. The theta value here gives us the degree of intrinsic ability we measure.

Applications

The IRT model can be successfully applied in many assessment settings (psychology, education, health outcome research, etc.). It can also be used to design and improve scales or measures by including highly discriminative items that help measure accuracy and reduce the burden of answering long questionnaires. Since the unit of analysis of IRT models is the item, they can be utilised to compare different measured items, as long as they measure the same underlying structure. Furthermore, they can be used in different functions of items to assess why calibrated and tested items always behave differently between groups. This can lead to studies identifying agents responsible for differences in responses and linking them to population characteristics. Finally, they can be employed for computer adaptive testing.

Conclusion

The Item Response Theory program demonstrates the probability that a person with skill X will possess a potential to perform at level Y. Because the educational or psychological structure being measured is mostly physically imperceptible (latent), and because the structure being measured can become symbolic.

IRT is not a terminology used to express a single theory or method. It emphasises a family of theories and methods, and a fairly large one, with many other terms used to distinguish specific methods.

Difficulty: A feature that is not easy to reach, solve, or understand.

Discrimination: The level to which an item differentiate between persons with a higher or lower level of a trait, potential, or whatever is measured.

Latent trait patterns vary remarkably from CTT. In the CTT, there are no assumptions made about the frequency distribution of test scores. This assumption is inherent in latent property models.