Parameter Estimation Bias of Dichotomous Logistic Item Response Theory Models Using Different Variables

Autor/inn/en	Köse, Alper; Dogan, C. Deha
Titel	Parameter Estimation Bias of Dichotomous Logistic Item Response Theory Models Using Different Variables
Quelle	In: International Journal of Evaluation and Research in Education, 8 (2019) 3, S.425-433 (9 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2252-8822
Schlagwörter	Statistical Bias; Item Response Theory; Simulation; Accuracy; Sample Size; Test Length; Statistical Distributions; Ability + Suchen Sie Ihr Suchwort? Item-Response-Theorie; Simulation program; Simulationsprogramm; Wahrscheinlichkeitsverteilung; Fähigkeit; Fertigkeit
Abstract	The aim of this study was to examine the precision of item parameter estimation in different sample sizes and test lengths under three parameter logistic model (3PL) item response theory (IRT) model, where the trait measured by a test was not normally distributed or had a skewed distribution. In the study, number of categories (1-0), and item response model were identified as fixed conditions, and sample size, test length variables, and the ability distributions were selected as manipulated conditions. This is a simulation study. So data simulation and data analysis were done via packages in the R programming language. Results of the study showed that item parameter estimations performed under normal distribution were much stronger and bias-free compared to non-normal distribution. Moreover, the sample size had some limited positive effect on parameter estimation. However, the test length had no effect parameter estimation. As a result the importance of normality assumptions for IRT models were highlighted and findings were discussed based on relevant literature. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01