Literaturnachweis - Detailanzeige
Autor/inn/en | Huang, Qi; Bolt, Daniel M. |
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Titel | Relative Robustness of CDMs and (M)IRT in Measuring Growth in Latent Skills |
Quelle | In: Educational and Psychological Measurement, 83 (2023) 4, S.808-830 (23 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
Zusatzinformation | ORCID (Huang, Qi) ORCID (Bolt, Daniel M.) |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
ISSN | 0013-1644 |
DOI | 10.1177/00131644221117194 |
Schlagwörter | Item Response Theory; Test Items; Skill Development; Robustness (Statistics); Diagnostic Tests; Intelligence Tests; Error of Measurement; Simulation; Correlation; Longitudinal Studies Item-Response-Theorie; Test content; Testaufgabe; Kompetenzentwicklung; Qualifikationsentwicklung; Widerstandsfähigkeit; Diagnostic test; Diagnostischer Test; Intelligence test; Intelligenztest; Messfehler; Simulation program; Simulationsprogramm; Korrelation; Longitudinal study; Longitudinal method; Longitudinal methods; Längsschnittuntersuchung |
Abstract | Previous studies have demonstrated evidence of latent skill continuity even in tests intentionally designed for measurement of binary skills. In addition, the assumption of binary skills when continuity is present has been shown to potentially create a lack of invariance in item and latent ability parameters that may undermine applications. In this article, we examine measurement of growth as one such application, and consider multidimensional item response theory (MIRT) as a competing alternative. Motivated by prior findings concerning the effects of skill continuity, we study the relative robustness of cognitive diagnostic models (CDMs) and (M)IRT models in the measurement of growth under both binary and continuous latent skill distributions. We find CDMs to be a less robust way of quantifying growth under misspecification, and subsequently provide a real-data example suggesting underestimation of growth as a likely consequence. It is suggested that researchers should regularly attend to the assumptions associated with the use of latent binary skills and consider (M)IRT as a potentially more robust alternative if unsure of their discrete nature. (As Provided). |
Anmerkungen | SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com |
Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2024/1/01 |