Gibbs Samplers for Logistic Item Response Models via the Pólya–Gamma Distribution: A Computationally Efficient Data-Augmentation Strategy
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,General Psychology
Link
http://link.springer.com/content/pdf/10.1007/s11336-018-9641-x.pdf
Reference55 articles.
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3. Baker, F. B., & Kim, S. H. (Eds.). (2004). Item response theory: Parameter estimation techniques. Boca Raton: CRC Press.
4. Biane, P., Pitman, J., & Yor, M. (2001). Probability laws related to the Jacobi theta and Riemann zeta functions, and Brownian excursions. Bulletin of the American Mathematical Society, 38(4), 435–465.
5. Bock, R. D., & Aitkin, M. (1981). Marginal maximum likelihood estimation of item parameters: Application of an EM algorithm. Psychometrika, 46(4), 443–459.
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