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Diagnostic tests for the distribution of random effects in multivariate mixed effects models

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  • Simos G. Meintanis
  • James S. Allison
  • Leonard Santana

Abstract

Fourier methods are proposed for testing the distribution of random effects in classical and robust multivariate mixed effects models. The test statistics involve estimation of the characteristic function of random effects. Theoretical and computational issues are addressed while Monte Carlo results show that the new procedures compare favorably with other methods.

Suggested Citation

  • Simos G. Meintanis & James S. Allison & Leonard Santana, 2016. "Diagnostic tests for the distribution of random effects in multivariate mixed effects models," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(1), pages 201-215, January.
  • Handle: RePEc:taf:lstaxx:v:45:y:2016:i:1:p:201-215
    DOI: 10.1080/03610926.2013.828073
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    Cited by:

    1. Simos G. Meintanis & James Allison & Leonard Santana, 2016. "Goodness-of-fit tests for semiparametric and parametric hypotheses based on the probability weighted empirical characteristic function," Statistical Papers, Springer, vol. 57(4), pages 957-976, December.

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