Psychometric data analysis: A size/fit trade-off evaluation procedure for knowledge structures

  • A crucial problem in knowledge space theory, a modern psychological test theory, is the derivation of a realistic knowledge structure representing the organization of knowledge in an information domain and examinee population under reference. Often, one is left with the problem of selecting among candidate competing knowledge structures. This article proposes a measure for the selection among competing knowledge structures. It is derived within an operational framework (prediction paradigm), and is partly based on the unitary method of proportional reduction in predictive error as advocated by the authors Guttman, Goodman, and Kruskal. In particular, this measure is designed to trade off the (descriptive) fit and size of a knowledge structure, which is of high interest in knowledge space theory. The proposed approach is compared with the Correlational Agreement Coefficient, which has been recently discussed for the selection among competing surmise relations. Their performances asA crucial problem in knowledge space theory, a modern psychological test theory, is the derivation of a realistic knowledge structure representing the organization of knowledge in an information domain and examinee population under reference. Often, one is left with the problem of selecting among candidate competing knowledge structures. This article proposes a measure for the selection among competing knowledge structures. It is derived within an operational framework (prediction paradigm), and is partly based on the unitary method of proportional reduction in predictive error as advocated by the authors Guttman, Goodman, and Kruskal. In particular, this measure is designed to trade off the (descriptive) fit and size of a knowledge structure, which is of high interest in knowledge space theory. The proposed approach is compared with the Correlational Agreement Coefficient, which has been recently discussed for the selection among competing surmise relations. Their performances as selection measures are compared in a simulation study using the fundamental basic local independence model in knowledge space theory.show moreshow less

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Metadaten
Author:Ali ÜnlüGND, Waqas Ahmed Malik
URN:urn:nbn:de:bvb:384-opus4-4950
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/625
Series (Serial Number):Preprints des Instituts für Mathematik der Universität Augsburg (2008-05)
Type:Preprint
Language:English
Publishing Institution:Universität Augsburg
Release Date:2008/02/06
Tag:Explorative Datenanalyse; Wissensraumtheorie; Latente-Variable-Modell; Auswahlkoeffizient
Exploratory data analysis; Knowledge space theory; Latent variable model; Selection measure
GND-Keyword:Testtheorie; Wissensrepräsentation; Diskrete Struktur; Explorative Datenanalyse
Institutes:Mathematisch-Naturwissenschaftlich-Technische Fakultät
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Mathematik
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 51 Mathematik / 510 Mathematik