El impacto de especificar incorrectamente la distribución de los efectos aleatorios en las estimaciones de modelos lineales generalizados mixtos
The impact of misspecifying random efects distribution on the estimation of generalized linear mixed models
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Resumen (es)
La inferencia en modelos lineales generalizados mixtos está basada principalmente en la teoría de máxima verosimilitud, la cual asume que las estructuras tanto para la parte de los efectos fijos como de los efectos aleatorios están correctamente especificadas. Algunos autores han mostrado la sensibilidad de las estimaciones de los efectos fijos a especificaciones incorrectas de los efectos aleatorios. El objetivo de esta investigación es identificar, vía simulación, el impacto de la especificación incorrecta de la distribución de los efectos aleatorios en los modelos lineales generalizados mixtos, específicamente para los casos de las distribuciones Poisson y Binomial NegativaResumen (en)
Inference in generalized linear mixed models is often based on maximum likelihood theory, which assumes that structures of both fixed effects and random effects is correctly specified. Some authors have shown sensitivity of estimates of fixed effects to random-effects misspecifications. This research aims to identify, using simulation, the impact of misspecifying random-effects distribution in generalized linear mixed models, specifically for the cases of Poisson and Negative Binomial distributions.
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