ERIC Number: EJ1231037
Record Type: Journal
Publication Date: 2019-Sep
Pages: 9
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-2252-8822
EISSN: N/A
Parameter Estimation Bias of Dichotomous Logistic Item Response Theory Models Using Different Variables
Köse, Alper; Dogan, C. Deha
International Journal of Evaluation and Research in Education, v8 n3 p425-433 Sep 2019
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.
Descriptors: Statistical Bias, Item Response Theory, Simulation, Accuracy, Sample Size, Test Length, Statistical Distributions, Ability
Institute of Advanced Engineering and Science. C5 Plumbon, Banguntapan, Yogyakarta, 55198, Indonesia. Tel: +62-274-4534501; Fax: +62-274-564604; e-mail: ijere@iaesjournal.com; Web site: http://ijere.iaescore.com/
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A