• Corpus ID: 245650288

Factor tree copula models for item response data

  title={Factor tree copula models for item response data},
  author={Sayed H. Kadhem and Aristidis K. Nikoloulopoulos},
Factor copula models for item response data are more interpretable and fit better than (truncated) vine copula models when dependence can be explained through latent variables, but are not robust to violations of conditional independence. To circumvent these issues, truncated vines and factor copula models for item response data are joined to define a combined model, the so called factor tree copula model, with individual benefits from each of the two approaches. Rather than adding factors and… 

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