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Journals / Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi / 2020 / Cilt: 11 - Sayı: 1

Item Parameter Estimation for Dichotomous Items Based on Item Response Theory: Comparison of BILOG-MG, Mplus and R (ltm)

Şeyma UYAR
Neşe ÖZTÜRK GÜBEŞ
Pages
27–42
Publication Date
2020-03-24
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

After looking at the resulting bias and root mean square error (RMSE) values, it can be concluded that Mplus is an unbiased program when compared to BILOG-MG and R (ltm).

📌 3 Key Takeaways

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Objective & Hypothesis:The aim of this study is twofold.
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Key Findings & Data:Another is to provide information about the performance of Mplus, BILOG-MG and R (ltm) programs in terms of parameter estimation under the conditions which were mentioned above.
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Conclusion & Impact:After looking at the resulting bias and root mean square error (RMSE) values, it can be concluded that Mplus is an unbiased program when compared to BILOG-MG and R (ltm).
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:IRT · parameter estimation · Mplus

Abstract

The aim of this study is twofold. The first one is to investigate the effect of sample size and test length on the estimation of item parameters and their standard errors for the two parameter item response theory (IRT). Another is to provide information about the performance of Mplus, BILOG-MG and R (ltm) programs in terms of parameter estimation under the conditions which were mentioned above. The simulated data were used in this study. The examinee responses were generated by using the open-source program R. After obtaining the data sets, the parameters were estimated in BILOG-MG, Mplus and R (ltm). The accuracy of the item parameters and ability estimates were evaluated under six conditions that differed in the numbers of items and examinees. After looking at the resulting bias and root mean square error (RMSE) values, it can be concluded that Mplus is an unbiased program when compared to BILOG-MG and R (ltm). BILOG-MG can estimate parameters and standard errors close to the true values, when compared to Mplus and R (ltm).

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Cite This Article

UYAR, Ş., GÜBEŞ, N. Ö. (2020). Item Parameter Estimation for Dichotomous Items Based on Item Response Theory: Comparison of BILOG-MG, Mplus and R (ltm). Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi, Cilt: 11 - Sayı: 1, 27–42. https://ajindex.com/articles/137305

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References (8)

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