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Consistent estimation in the rasch model based on nonparametric margins

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  • Dean Follmann

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  • Dean Follmann, 1988. "Consistent estimation in the rasch model based on nonparametric margins," Psychometrika, Springer;The Psychometric Society, vol. 53(4), pages 553-562, December.
    • Handle: RePEc:spr:psycho:v:53:y:1988:i:4:p:553-562
    DOI: 10.1007/BF02294407
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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. Heckman, James & Singer, Burton, 1984. "A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models for Duration Data," Econometrica, Econometric Society, vol. 52(2), pages 271-320, March.
    3. Paul Holland, 1981. "When are item response models consistent with observed data?," Psychometrika, Springer;The Psychometric Society, vol. 46(1), pages 79-92, March.
    4. Erling Andersen, 1980. "Comparing latent distributions," Psychometrika, Springer;The Psychometric Society, vol. 45(1), pages 121-134, March.
    5. Noel Cressie & Paul Holland, 1983. "Characterizing the manifest probabilities of latent trait models," Psychometrika, Springer;The Psychometric Society, vol. 48(1), pages 129-141, March.
    6. Erling Andersen & Mette Madsen, 1977. "Estimating the parameters of the latent population distribution," Psychometrika, Springer;The Psychometric Society, vol. 42(3), pages 357-374, September.
    7. Fienberg, Stephen E. & Meyer, Michael M., 1983. "Loglinear models and categorical data analysis with psychometric and econometric applications," Journal of Econometrics, Elsevier, vol. 22(1-2), pages 191-214.
    8. Robert Mislevy, 1984. "Estimating latent distributions," Psychometrika, Springer;The Psychometric Society, vol. 49(3), pages 359-381, September.
    9. repec:cor:louvrp:-271 is not listed on IDEAS
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    Citations

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    Cited by:

    1. Matthias Davier & Shelby Haberman, 2014. "Hierarchical Diagnostic Classification Models Morphing into Unidimensional ‘Diagnostic’ Classification Models—A Commentary," Psychometrika, Springer;The Psychometric Society, vol. 79(2), pages 340-346, April.
    2. David J. Hessen, 2010. "Likelihood Ratio Tests for Special Rasch Models," Journal of Educational and Behavioral Statistics, , vol. 35(6), pages 611-628, December.
    3. David J. Hessen, 2023. "Fitting and Testing Log-Linear Subpopulation Models with Known Support," Psychometrika, Springer;The Psychometric Society, vol. 88(3), pages 917-939, September.
    4. E. Maris, 1998. "On the sampling interpretation of confidence intervals and hypothesis tests in the context of conditional maximum likelihood estimation," Psychometrika, Springer;The Psychometric Society, vol. 63(1), pages 65-71, March.
    5. Matthias von Davier, 2021. "Commentary: Matching IRT Models to PRO Constructs— Modeling Alternatives, and Some Thoughts on What Makes a Model Different," Psychometrika, Springer;The Psychometric Society, vol. 86(3), pages 825-832, September.
    6. Paul Holland, 1990. "On the sampling theory roundations of item response theory models," Psychometrika, Springer;The Psychometric Society, vol. 55(4), pages 577-601, December.
    7. N. Verhelst & C. Glas, 1993. "A dynamic generalization of the Rasch model," Psychometrika, Springer;The Psychometric Society, vol. 58(3), pages 395-415, September.
    8. Cees Glas, 1999. "Modification indices for the 2-PL and the nominal response model," Psychometrika, Springer;The Psychometric Society, vol. 64(3), pages 273-294, September.
    9. Anton K. Formann & Thomas Kohlmann, 1998. "Structural Latent Class Models," Sociological Methods & Research, , vol. 26(4), pages 530-565, May.
    10. Anders Skrondal & Sophia Rabe‐Hesketh, 2007. "Latent Variable Modelling: A Survey," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(4), pages 712-745, December.

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