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Joint consistency of nonparametric item characteristic curve and ability estimation

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  • Jeff Douglas

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  • Jeff Douglas, 1997. "Joint consistency of nonparametric item characteristic curve and ability estimation," Psychometrika, Springer;The Psychometric Society, vol. 62(1), pages 7-28, March.
    • Handle: RePEc:spr:psycho:v:62:y:1997:i:1:p:7-28
    DOI: 10.1007/BF02294778
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    References listed on IDEAS

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    1. J. Ramsay & S. Winsberg, 1991. "Maximum marginal likelihood estimation for semiparametric item analysis," Psychometrika, Springer;The Psychometric Society, vol. 56(3), pages 365-379, September.
    2. J. Ramsay, 1991. "Kernel smoothing approaches to nonparametric item characteristic curve estimation," Psychometrika, Springer;The Psychometric Society, vol. 56(4), pages 611-630, December.
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    Citations

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    Cited by:

    1. Michael Peress, 2012. "Identification of a Semiparametric Item Response Model," Psychometrika, Springer;The Psychometric Society, vol. 77(2), pages 223-243, April.
    2. Benjamin Williams, 2019. "Identification of a nonseparable model under endogeneity using binary proxies for unobserved heterogeneity," Quantitative Economics, Econometric Society, vol. 10(2), pages 527-563, May.
    3. Brian Habing & Louis Roussos, 2003. "On the need for negative local item dependence," Psychometrika, Springer;The Psychometric Society, vol. 68(3), pages 435-451, September.
    4. Hongwen Guo & Sandip Sinharay, 2011. "Nonparametric Item Response Curve Estimation With Correction for Measurement Error," Journal of Educational and Behavioral Statistics, , vol. 36(6), pages 755-778, December.
    5. William Stout, 2002. "Psychometrics: From practice to theory and back," Psychometrika, Springer;The Psychometric Society, vol. 67(4), pages 485-518, December.
    6. Johnson, Matthew S., 2007. "Modeling dichotomous item responses with free-knot splines," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4178-4192, May.
    7. Mazza, Angelo & Punzo, Antonio & McGuire, Brian, 2014. "KernSmoothIRT: An R Package for Kernel Smoothing in Item Response Theory," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 58(i06).
    8. Thum, Anna-Elisabeth, 2013. "Psychology in econometric models: conceptual and methodological foundations," MPRA Paper 52293, University Library of Munich, Germany.
    9. Theo Eggen & Norman Verhelst, 2006. "Loss of Information in Estimating Item Parameters in Incomplete Designs," Psychometrika, Springer;The Psychometric Society, vol. 71(2), pages 303-322, June.
    10. Xueli Xu & Jeff Douglas, 2006. "Computerized adaptive testing under nonparametric IRT models," Psychometrika, Springer;The Psychometric Society, vol. 71(1), pages 121-137, March.
    11. Chen, Yunxiao & Lu, Yan & Moustaki, Irini, 2022. "Detection of two-way outliers in multivariate data and application to cheating detection in educational tests," LSE Research Online Documents on Economics 112499, London School of Economics and Political Science, LSE Library.
    12. Jeffrey Douglas, 2001. "Asymptotic identifiability of nonparametric item response models," Psychometrika, Springer;The Psychometric Society, vol. 66(4), pages 531-540, December.
    13. Yang Liu & Weimeng Wang, 2022. "Semiparametric Factor Analysis for Item-Level Response Time Data," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 666-692, June.

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