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Factors affecting the variability of IRT equating coefficients

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  • Michela Battauz

Abstract

type="main" xml:id="stan12048-abs-0001"> Knowing the effect of the factors that can influence the variability of the equating coefficients is an important tool for the development of the linkage plans. This paper explores the effect of various factors on the variability of item response theory equating coefficients. The factors studied are the sample size, the number of common items, the length of the chain, and the possibility of averaging the equating transformations related to different paths that connect the same two forms. Both asymptotic and simulations results are provided.

Suggested Citation

  • Michela Battauz, 2015. "Factors affecting the variability of IRT equating coefficients," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 69(2), pages 85-101, May.
    • Handle: RePEc:bla:stanee:v:69:y:2015:i:2:p:85-101
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    File URL: http://hdl.handle.net/10.1111/stan.12048
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    References listed on IDEAS

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    1. R. Bock & Murray Aitkin, 1981. "Marginal maximum likelihood estimation of item parameters: Application of an EM algorithm," Psychometrika, Springer;The Psychometric Society, vol. 46(4), pages 443-459, December.
    2. Rizopoulos, Dimitris, 2006. "ltm: An R Package for Latent Variable Modeling and Item Response Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 17(i05).
    3. Michela Battauz, 2013. "IRT Test Equating in Complex Linkage Plans," Psychometrika, Springer;The Psychometric Society, vol. 78(3), pages 464-480, July.
    4. Ogasawara, Haruhiko, 2000. "Asymptotic Standard Errors of IRT Equating Coefficients Using Moments," 商学討究 (Shogaku Tokyu), Otaru University of Commerce, vol. 51(1), pages 1-23.
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    Cited by:

    1. Alexander Robitzsch, 2023. "Linking Error in the 2PL Model," J, MDPI, vol. 6(1), pages 1-27, January.
    2. Alexander Robitzsch, 2024. "Estimation of Standard Error, Linking Error, and Total Error for Robust and Nonrobust Linking Methods in the Two-Parameter Logistic Model," Stats, MDPI, vol. 7(3), pages 1-21, June.
    3. Alexander Robitzsch, 2020. "L p Loss Functions in Invariance Alignment and Haberman Linking with Few or Many Groups," Stats, MDPI, vol. 3(3), pages 1-38, August.
    4. Michela Battauz, 2023. "Testing for differences in chain equating," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 77(2), pages 134-145, May.

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