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Confidence Distribution for the Ability Parameter of the Rasch Model

Author

Listed:
  • Piero Veronese

    (Bocconi University)

  • Eugenio Melilli

    (Bocconi University)

Abstract

In this paper, we consider the Rasch model and suggest novel point estimators and confidence intervals for the ability parameter. They are based on a proposed confidence distribution (CD) whose construction has required to overcome some difficulties essentially due to the discrete nature of the model. When the number of items is large, the computations due to the combinatorics involved become heavy, and thus, we provide first- and second-order approximations of the CD. Simulation studies show the good behavior of our estimators and intervals when compared with those obtained through other standard frequentist and weakly informative Bayesian procedures. Finally, using the expansion of the expected length of the suggested interval, we are able to identify reasonable values of the sample size which lead to a desired length of the interval.

Suggested Citation

  • Piero Veronese & Eugenio Melilli, 2021. "Confidence Distribution for the Ability Parameter of the Rasch Model," Psychometrika, Springer;The Psychometric Society, vol. 86(1), pages 131-166, March.
  • Handle: RePEc:spr:psycho:v:86:y:2021:i:1:d:10.1007_s11336-021-09747-4
    DOI: 10.1007/s11336-021-09747-4
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    References listed on IDEAS

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    1. Yang Liu & Jan Hannig, 2016. "Generalized Fiducial Inference for Binary Logistic Item Response Models," Psychometrika, Springer;The Psychometric Society, vol. 81(2), pages 290-324, June.
    2. David Andrich, 2010. "Sufficiency and Conditional Estimation of Person Parameters in the Polytomous Rasch Model," Psychometrika, Springer;The Psychometric Society, vol. 75(2), pages 292-308, June.
    3. Robert Jannarone & Kai Yu & James Laughlin, 1990. "Easy bayes estimation for rasch-type models," Psychometrika, Springer;The Psychometric Society, vol. 55(3), pages 449-460, September.
    4. Mair, Patrick & Hatzinger, Reinhold, 2007. "Extended Rasch Modeling: The eRm Package for the Application of IRT Models in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 20(i09).
    5. Karl Klauer, 1991. "Exact and best confidence intervals for the ability parameter of the Rasch model," Psychometrika, Springer;The Psychometric Society, vol. 56(3), pages 535-547, September.
    6. David Thissen & Howard Wainer, 1982. "Some standard errors in item response theory," Psychometrika, Springer;The Psychometric Society, vol. 47(4), pages 397-412, December.
    7. Min-ge Xie & Kesar Singh, 2013. "Confidence Distribution, the Frequentist Distribution Estimator of a Parameter: A Review," International Statistical Review, International Statistical Institute, vol. 81(1), pages 3-39, April.
    8. Piero Veronese & Eugenio Melilli, 2015. "Fiducial and Confidence Distributions for Real Exponential Families," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(2), pages 471-484, June.
    9. Hariharan Swaminathan & Janice Gifford, 1985. "Bayesian estimation in the two-parameter logistic model," Psychometrika, Springer;The Psychometric Society, vol. 50(3), pages 349-364, September.
    10. Haruhiko Ogasawara, 2012. "Asymptotic expansions for the ability estimator in item response theory," Computational Statistics, Springer, vol. 27(4), pages 661-683, December.
    11. Thomas Warm, 1989. "Weighted likelihood estimation of ability in item response theory," Psychometrika, Springer;The Psychometric Society, vol. 54(3), pages 427-450, September.
    12. Anna Doebler & Philipp Doebler & Heinz Holling, 2013. "Optimal and Most Exact Confidence Intervals for Person Parameters in Item Response Theory Models," Psychometrika, Springer;The Psychometric Society, vol. 78(1), pages 98-115, January.
    13. Ogasawara, Haruhiko, 2012. "Supplement to the paper“ Asymptotic expansions for the ability estimator in item response theory”," 商学討究 (Shogaku Tokyu), Otaru University of Commerce, vol. 63(2/3), pages 329-336.
    14. Jan Hannig & Hari Iyer & Randy C. S. Lai & Thomas C. M. Lee, 2016. "Generalized Fiducial Inference: A Review and New Results," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(515), pages 1346-1361, July.
    15. Tore Schweder & Nils Lid Hjort, 2002. "Confidence and Likelihood," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 29(2), pages 309-332, June.
    16. Deheuvels, Paul & Puri, Madan L. & Ralescu, Stefan S., 1989. "Asymptotic expansions for sums of nonidentically distributed Bernoulli random variables," Journal of Multivariate Analysis, Elsevier, vol. 28(2), pages 282-303, February.
    17. Frederic Lord, 1983. "Unbiased estimators of ability parameters, of their variance, and of their parallel-forms reliability," Psychometrika, Springer;The Psychometric Society, vol. 48(2), pages 233-245, June.
    18. Jan Hannig & Thomas C. M. Lee, 2009. "Generalized fiducial inference for wavelet regression," Biometrika, Biometrika Trust, vol. 96(4), pages 847-860.
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