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What is classical test theory?

What is classical test theory?

Classical test theory, also known as true score theory, assumes that each person has a true score, T, that would be obtained if there were no errors in measurement. A person’s true score is defined as the expected score over an infinite number of independent administrations of the scale.

What is classical test theory example?

It is the proportion of test takers who answered correctly out of the total number of test takers. For example, an item difficulty score of 89/100 means that out of 100 people, 89 answered correctly.

Who came up with classical test theory?

Charles Spearman was one of the founders of this classical test theory, having an understanding that there were generally always going to be errors in test measurements, that these errors are random variables, and finally, that they could be correlated and indexed.

What is the classical theory of measurement?

According to classical measurement theory, the reliability of an instrument refers to the relationship between the true score and the observed score. Because the true score is unknown, reliability must be estimated by other means, typically through the correlations of parallel tests.

What is the basic assumption of classical test theory?

Classical test theory assumes linearity—that is, the regression of the observed score on the true score is linear. This linearity assumption underlies the practice of creating tests from the linear combination of items or subtests.

What is classical test theory and item response?

Classical Test Theory and Item Response Theory (CTT & IRT) are the two primary psychometric paradigms. That is, they are mathematical approaches to how tests are analyzed and scored. They differ quite substantially in substance and complexity, even though they both nominally do the same thing.

What are CTT and IRT?

What are the limitations of classical test theory?

The vast majority of IS studies uses classical test theory (CTT), but this approach suffers from three major theoretical shortcomings: (1) it assumes a linear relationship between the latent variable and observed scores, which rarely represents the empirical reality of behavioral constructs; (2) the true score can …

What is reliability in classical test theory?

In CTT , reliability is defined as the proportion of true score variance to total variance . It is most often estimated using the coefficient \alpha .

What is the difference between IRT and CTT?

The most important difference between CTT and IRT is that in CTT, one uses a common estimate of the measurement precision that is assumed to be equal for all individuals irrespective of their attribute levels. In IRT, however, the measurement precision depends on the latent-attribute value.

What are the salient characteristics of classical test theory?

Which is better CTT or IRT?

Preliminary results revealed that IRT is indeed superior to CTT in individual change detection, provided that the tests consist of at least 20 items. For shorter tests, however, CTT is generally better at correctly detecting change in individuals.

Classical test theory is defined such that any observed test score, X, is the sum of a true score, T, and a random error, E. R.L. Brennan, in International Encyclopedia of Education (Third Edition), 2010

Can Bayesian theory be used to estimate classical item and test parameters?

Direct application of standard likelihood or Bayesian theory to the estimation of classical item and test parameters is therefore less straightforward. Fortunately, nearly all classical parameters are defined in terms of first-order and second-order (product) moments of score distributions.

What is the relationship between classical test theory and generalizability theory?

Classical test theory and ANOVA can be viewed as the parents of generalizability theory, but the child is both more and less than the simple conjunction of its parents. For example, although generalizability theory liberalizes classical test theory, not all aspects of classical theory are incorporated in generalizability theory.