Classical test theory (CTT) is a body of related psychometric theory that predicts outcomes of psychological testing such as the difficulty of items or the ability of test-takers. It is a theory of testing based on the idea that a person's observed or obtained score on a test is the sum of a true score (error-free score) and an error score. Generally speaking, the aim of classical test theory is to understand and improve the reliability of psychological tests.
Classical test theory may be regarded as roughly synonymous with true score theory. The term "classical" refers not only to the chronology of these models but also contrasts with the more recent psychometric theories, generally referred to collectively as item response theory, which sometimes bear the appellation "modern" as in "modern latent trait theory".
Classical test theory as we know it today was codified by Novick (1966) and described in classic texts such as Lord & Novick (1968) and Allen & Yen (1979/2002). The description of classical test theory below follows these seminal publications.
Classical test theory was born only after the following three achievements or ideas were conceptualized:
a recognition of the presence of errors in measurements,
a conception of that error as a random variable,
a conception of correlation and how to index it.
In 1904, Charles Spearman was responsible for figuring out how to correct a correlation coefficient for attenuation due to measurement error and how to obtain the index of reliability needed in making the correction. Spearman's finding is thought to be the beginning of Classical Test Theory by some (Traub, 1997). Others who had an influence in the Classical Test Theory's framework include: George Udny Yule, Truman Lee Kelley, Fritz Kuder & Marion Richardson involved in making the Kuder–Richardson Formulas, Louis Guttman, and, most recently, Melvin Novick, not to mention others over the next quarter century after Spearman's initial findings.
Cette page est générée automatiquement et peut contenir des informations qui ne sont pas correctes, complètes, à jour ou pertinentes par rapport à votre recherche. Il en va de même pour toutes les autres pages de ce site. Veillez à vérifier les informations auprès des sources officielles de l'EPFL.
Classical test theory (CTT) is a body of related psychometric theory that predicts outcomes of psychological testing such as the difficulty of items or the ability of test-takers. It is a theory of testing based on the idea that a person's observed or obtained score on a test is the sum of a true score (error-free score) and an error score. Generally speaking, the aim of classical test theory is to understand and improve the reliability of psychological tests. Classical test theory may be regarded as roughly synonymous with true score theory.
In psychometrics, item response theory (IRT) (also known as latent trait theory, strong true score theory, or modern mental test theory) is a paradigm for the design, analysis, and scoring of tests, questionnaires, and similar instruments measuring abilities, attitudes, or other variables. It is a theory of testing based on the relationship between individuals' performances on a test item and the test takers' levels of performance on an overall measure of the ability that item was designed to measure.
vignette|Ça permet de rendre pour nos rencontres.Aide également un lieu de référence pour l'apprentissage. L’Educational Testing Service (« service d’évaluation éducatif », abrégé ETS), fondé en 1947, est la plus grande organisation à but non lucratif privée de mesure et d’évaluation éducative au monde. Elle fonctionne avec un budget annuel d’environ 900 millions de dollars. Son siège social se situe à Lawrence Township, New Jersey, non loin de Princeton.
This course is neither an introduction to the mathematics of statistics nor an introduction to a statistics program such as R. The aim of the course is to understand statistics from its experimental d
This course discusses quantitatively some important and generic performance and reliability issues that affect the behaviour of supply chains, and in particular manufacturing systems.
Explore les enquêtes spatiales de John Snow sur les épidémies de choléra, remettant en question les croyances dominantes et révolutionnant l'épidémiologie.
Explore le suivi des connaissances bayésiennes, les modèles linéaires généralisés et les algorithmes de clustering pour la découverte de structures dans les données comportementales.