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Autor/inn/enFinkelman, Matthew D.; Weiss, David J.; Kim-Kang, Gyenam
TitelItem Selection and Hypothesis Testing for the Adaptive Measurement of Change
QuelleIn: Applied Psychological Measurement, 34 (2010) 4, S.238-254 (17 Seiten)
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Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN0146-6216
DOI10.1177/0146621609344844
SchlagwörterComputer Assisted Testing; Hypothesis Testing; Measurement; Item Analysis; Test Items; Psychological Studies; Evaluation Methods; Comparative Analysis; Measurement Techniques; Error Patterns; Item Response Theory; Test Construction; Simulation; Change; Item Banks
AbstractAssessing individual change is an important topic in both psychological and educational measurement. An adaptive measurement of change (AMC) method had previously been shown to exhibit greater efficiency in detecting change than conventional nonadaptive methods. However, little work had been done to compare different procedures within the AMC framework. This study introduced a new item selection criterion and two new test statistics for detecting change with AMC that were specifically designed for the paradigm of hypothesis testing. In two simulation sets, the new methods for detecting significant change improved on existing procedures by demonstrating better adherence to Type I error rates and substantially better power for detecting relatively small change. (Contains 3 tables and 4 figures.) (As Provided).
AnmerkungenSAGE 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: http://sagepub.com
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2017/4/10
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