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Autor/inn/enSengul Avsar, Asiye; Tavsancil, Ezel
TitelExamination of Polytomous Items' Psychometric Properties According to Nonparametric Item Response Theory Models in Different Test Conditions
QuelleIn: Educational Sciences: Theory and Practice, 17 (2017) 2, S.493-514 (22 Seiten)
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Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN1303-0485
SchlagwörterTest Items; Psychometrics; Nonparametric Statistics; Item Response Theory; Models; Monte Carlo Methods; Goodness of Fit; Test Reliability; Sample Size; Test Length; Likert Scales; Error of Measurement; Statistical Distributions
AbstractThis study analysed polytomous items' psychometric properties according to nonparametric item response theory (NIRT) models. Thus, simulated datasets--three different test lengths (10, 20 and 30 items), three sample distributions (normal, right and left skewed) and three samples sizes (100, 250 and 500)--were generated by conducting 20 replications in 27 test conditions. Via simulated datasets, polytomous items' psychometric properties were investigated through NIRT models, the Mokken Homogeneity Model (MHM) and the Kernel Smoothing Approach Model (KSAM). According to MHM analysis results, number of items, distribution of sample and sample-size factors affected items' level of fit. As a result of scaling data according to MHM in this study's test conditions, tests that generally fit MHM at weak and moderate levels, with high reliability, were achieved. According to KSAM analysis results, number of items, sample distribution and sample-size factors influenced item and test discrimination. Consequent to KSAM data analysis, tests that generally consisted of items with an acceptable discrimination level and with high reliability were achieved. In this study, producing H coefficients, through MHM, that were easy to interpret and providing, through KSAM, graphics with detailed information made it easier to examine complementary polytomous items' psychometric properties. (As Provided).
AnmerkungenEducational Consultancy, Ltd (EDAM). Kisikli Mh. Alemdag Cd. Yan Yol Sk., SBK Is Merkezi No:5 Kat:1, Uskudar-Istanbul, 34692 Turkey. Tel: +90-216-481-30-23; Fax: +90-216-481-31-36; e-mail: editor@edam.com.tr; Web site: http://www.estp.com.tr/
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2020/1/01
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