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Bayesian Estimation of a Multilevel IRT Model Using Gibbs Sampling
4 references·16 citing·44 second hopsampled
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References

  • 1981Marginal Maximum Likelihood Estimation of Item Parameters: Application of an EM Algorithm2,338 cited
  • 1992Full-Information Item Bi-Factor Analysis599 cited
  • 1999A Straightforward Approach to Markov Chain Monte Carlo Methods for Item Response Models476 cited
  • 1992Bayesian Estimation of Normal Ogive Item Response Curves Using Gibbs Sampling419 cited

Cited by

  • 2001MCMC Estimation and Some Model-Fit Analysis of Multidimensional IRT Models349 cited
  • 2009Measuring progressions: Assessment structures underlying a learning progression330 cited
  • 2009High-dimensional Exploratory Item Factor Analysis by A Metropolis–Hastings Robbins–Monro Algorithm324 cited
  • 2009Psychometric approaches for developing commensurate measures across independent studies: Traditional and new models.282 cited
  • 2008Using Item Response Theory to Measure Extreme Response Style in Marketing Research: A Global Investigation271 cited
  • 2017Recent Methods for the Study of Measurement Invariance With Many Groups260 cited
  • 2003A nonlinear mixed model framework for item response theory.238 cited
  • 2004Resisting the Lonely Superpower: Responses of States in the United Nations to U.S. Dominance188 cited
  • 2009Modeling life-span growth curves of cognition using longitudinal data with multiple samples and changing scales of measurement.177 cited

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2007
Relaxing Measurement Invariance in Cross-National Consumer Research Using a Hierarchical IRT Model
175 cited
  • 2005High-Dimensional Maximum Marginal Likelihood Item Factor Analysis by Adaptive Quadrature174 cited
  • 2008A Multivariate Multilevel Approach to the Modeling of Accuracy and Speed of Test Takers166 cited
  • 2008Pooling data from multiple longitudinal studies: The role of item response theory in integrative data analysis.159 cited
  • 2007Latent Variable Modelling: A Survey*135 cited
  • 2011Road Maps for Learning: A Guide to the Navigation of Learning Progressions130 cited
  • 2008Item response theory facilitated cocalibrating cognitive tests and reduced bias in estimated rates of decline128 cited