Likelihood for random-effect models

• Autores: Youngjo Lee, John A. Nelder
• Localización: Sort: Statistics and Operations Research Transactions, ISSN 1696-2281, Vol. 29, Nº. 2, 2005, págs. 141-182
• Idioma: inglés
• Títulos paralelos:
  • Verosimilitud para modelos de efectos aleatorios (con discusión).
• Enlaces
  • Texto completo (pdf)
• Resumen

  • HolaFor inferences from random-effect models Lee and Nelder (1996) proposed to use hierarchical likelihood (h-likelihood). It allows inference from models that may include both fixed and random parameters. Because of the presence of unobserved random variables h-likelihood is not a likelihood in the Fisherian sense. The Fisher likelihood framework has advantages such as generality of application, statistical and computational efficiency. We introduce an extended likelihood framework and discuss why it is a proper extension, maintaining the advantages of the original likelihood framework.

    The new framework allows likelihood inferences to be drawn for a much wider class of models.

    MSC: 62F10 62F15 62F30 Keywords: generalized linear models, hierarchical models, h-likelihood HolaPer a la infer`encia en models amb efectes aleatoris Lee i Nelder (1996) proposaren utilitzar la versemblanc¿a jer`arquica (h-versemblanc¿a). Aquesta permet la infer`encia en models que presenten a la vegada par`ametres fixos i aleatoris. Per la pres`encia de variables aleat`ories no observables, la h-versemblanc¿a no ¿es una versemblanc¿a en el sentit Fisheri`a. El marc de refer`encia de la versemblanc¿a de Fisher t¿e avantatges com la generalitat d¿aplicaci¿o, l¿efici`encia estad¿ýstica i computacional. Nosaltres introdu¿ým un marc de versemblanc¿a ampliat i discutim perqu`e ¿es una extensi¿o apropiada, mantenint els avantatges del marc de la versemblanc¿a original. El nou marc de refer`encia permet fer infer`encies versemblants per a una classe m¿es `amplia de models.

    Paraules clau: models lineals generalitzats, models jer`arquics, h-versemblances

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