Influence diagnostics in mixed effects logistic regression models

• Alejandra Tapia ^[1] ; Victor Leiva ^[2] ; Maria del Pilar Diaz ^[3] ; Viviana Giampaoli ^[4]
  1. [1] Universidad Austral de Chile

     Universidad Austral de Chile

     Valdivia, Chile

     
  2. [2] Pontificia Universidad Católica de Valparaíso

     Pontificia Universidad Católica de Valparaíso

     Valparaíso, Chile

     
  3. [3] Universidad Nacional de Córdoba

     Universidad Nacional de Córdoba

     Argentina

     
  4. [4] Universidade de São Paulo

     Universidade de São Paulo

     Brasil

     

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• Localización: Test: An Official Journal of the Spanish Society of Statistics and Operations Research, ISSN-e 1863-8260, ISSN 1133-0686, Vol. 28, Nº. 3, 2019, págs. 920-942
• Idioma: inglés
• DOI: 10.1007/s11749-018-0613-3
• Texto completo no disponible (Saber más ...)
• Resumen

  • Correlated binary responses are commonly described by mixed effects logistic regression models. This article derives a diagnostic methodology based on the Q-displacement function to investigate local influence of the responses in the maximum likelihood estimates of the parameters and in the predictive performance of the mixed effects logistic regression model. An appropriate perturbation strategy of the probability of success is established, as a form of assessing the perturbation in the response. The diagnostic methodology is evaluated with Monte Carlo simulations. Illustrations with two real-world data sets (balanced and unbalanced) are conducted to show the potential of the proposed methodology.