Self-esteem is a personality trait that can be measured by both classical test theory and item response theory perspective. It reflects the overall subjective emotional evaluation of an individual’s worth to himself or herself. Scholars have described it as the attitude of an individual towards self. This belief in oneself can be measured on a scale of emotional states which can be calibrated in any of the two perspectives above. However, there is a major difference in the perspective that exist when self-esteem when measured using either the classical test theory perspective or item-response theory perspective.
The classical test theory is widely used in the psychometric test to recognize and develop reliability in psychological tests assessments. The classical theory is a model on the premise that testing of an attitude or behavior of an individual is observed by obtaining the sum of a true score and an error score (Kline, 2005). This test calculates the reliability of a psychological test by understanding and improving on any errors that might exist in the score from the observer’s perspective. The amount of error identified in a person’s attitude or self-trust allows the observer to determine the actual self-esteem that exists in an individual’s personality since the observer would be able to identify any errors that present in the observation.
This theory was developed by Charles Spearman who acknowledged that in any psychological observation, there were always tendencies of coming up with certain errors. He, therefore, developed the framework of this model to focus on identifying most of these errors in the measurement of personal attributes such as self-esteem as random variables. The model focuses on correlating and indexing most of these errors to make improvements and reduce some of these errors to increase the reliability of the psychological tests. According to Spearman, the main aim of the classical theory was to improve the reliability of the tests to yield a more-true score in psychometric measurements.
The Item Response Theory, on the other hand, is a conceptual measurement model that assigns numbers to psychometric measure following particular rules or pattern. The model attempts to simplify a rather complex psychological observation by assigning numbers to each observation based on the intensity of the behavior or attitude ("A Conceptual Introduction to Item Response Theory: Part 1. The Logic of IRT Scoring", 2018). When using IRT model, psychometrics base their observation on measurable characteristics such as means, proportions, and correlation. In the case of self-esteem as a variable, for instance, the observer would calibrate each attitude or behavior of an individual on a scale based on its intensity from a mean.
Despite the Item Response Theory being simple to use, it lacks in sophistication make it inappropriate to be used in a complex situation. When measuring self-esteem in an individual using IRT, the result would be independent to the sample within a linear transformation. Secondly, it has a weak linking or equating of variables especially when observing two or more complex individuals ("A Conceptual Introduction to Item Response Theory: Part 2. IRT Is a Probability Model", 2018). Lastly, the use of IRT makes it difficult to compare variables since the results found are not actual.
In conclusion, the results from the two models vary in accuracy and reliability. In most cases, CTT has been preferred over IRT since the results gotten are reliable and easily comparable. It is also easy to use CTT in observing complex variables such as self-esteem in this case since it gives the observer an opportunity to identify any errors that might be existing in the psychometric measurement.
References
Kline, T. J. B. (2005). Classical test theory: Assumptions, equations, limitations, and item analyses. Psychological testing: A practical approach to design and evaluation, 91-105.
A Conceptual Introduction to Item Response Theory: Part 1. The Logic of IRT Scoring. (2018). Retrieved from https://www.youtube.com/watch?v=SrdbllMYq8M
A Conceptual Introduction to Item Response Theory: Part 2. IRT Is a Probability Model. (2018). Retrieved from https://www.youtube.com/watch?v=b6FKYV1-mEU
