Consider a generalized linear model with a canonical link function, containing both fixed and random effects. In this paper, we consider inference about the fixed effects based on a conditional likelihood function. It is shown that this conditional likelihood function is valid for any distribution of the random effects and, hence, the resulting inferences about the fixed effects are insensitive to misspecification of the random effects distribution. Inferences based on the conditional likelihood are compared to those based on the likelihood function of the mixed effects model.

Conditional likelihood inference in generalized linear mixed models.

Sartori, Nicola;
2002

Abstract

Consider a generalized linear model with a canonical link function, containing both fixed and random effects. In this paper, we consider inference about the fixed effects based on a conditional likelihood function. It is shown that this conditional likelihood function is valid for any distribution of the random effects and, hence, the resulting inferences about the fixed effects are insensitive to misspecification of the random effects distribution. Inferences based on the conditional likelihood are compared to those based on the likelihood function of the mixed effects model.
File in questo prodotto:
File Dimensione Formato  
WP_2002_15.pdf

accesso aperto

Licenza: Non specificato
Dimensione 46.58 MB
Formato Adobe PDF
46.58 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3442395
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact