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Accurate estimation for extra-Poisson variability assuming random effect models.
de Oliveira, Ricardo Puziol; Achcar, Jorge Alberto.
Afiliación
  • de Oliveira RP; Medical School, University of São Paulo, Ribeirão Preto, Brazil.
  • Achcar JA; Medical School, University of São Paulo, Ribeirão Preto, Brazil.
J Appl Stat ; 48(16): 2982-3001, 2021.
Article en En | MEDLINE | ID: mdl-35707251
In this study, the components of extra-Poisson variability are estimated assuming random effect models under a Bayesian approach. A standard existing methodology to estimate extra-Poisson variability assumes a negative binomial distribution. The obtained results show that using the proposed random effect model it is possible to get more accurate estimates for the extra-Poisson variability components when compared to the use of a negative binomial distribution where it is possible to estimate only one component of extra-Poisson variability. Some illustrative examples are introduced considering real data sets.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Clinical_trials Idioma: En Revista: J Appl Stat Año: 2021 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Clinical_trials Idioma: En Revista: J Appl Stat Año: 2021 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Reino Unido