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1 results

  • Bayesian Analysis of Multivariate Probit Models with Surrogate Outcome Data

  • Wai-Yin Poon, Hai-Bin Wang
  • Journal:
    Psychometrika / Volume 75 / Issue 3 / September 2010
    Published online by Cambridge University Press:
    01 January 2025, pp. 498-520

  • A new class of parametric models that generalize the multivariate probit model and the errors-in-variables model is developed to model and analyze ordinal data. A general model structure is assumed to accommodate the information that is obtained via surrogate variables. A hybrid Gibbs sampler is developed to estimate the model parameters. To obtain a rapidly converged algorithm, the parameter expansion technique is applied to the correlation structure of the multivariate probit models. The proposed model and method of analysis are demonstrated with real data examples and simulation studies.