A data transformation to deal with constant under/over-dispersion in Poisson and binomial regression models

DOI10.1080/00949655.2020.1749276OpenAlexW3015824466MaRDI QIDQ5036854

Luz Marina Rondon, Luis Hernando Vanegas

Publication date: 23 February 2022

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2020.1749276

zbMATH Keywords

count databinomialPoissondata transformationover-dispersionunder-dispersionproportions

Mathematics Subject Classification ID

Generalized linear models (logistic models) (62J12) Statistics (62-XX)

Uses Software

• R
• Fahrmeir

Cites Work

• A hyper-Poisson regression model for overdispersed and underdispersed count data
• A flexible regression model for count data
• Asymptotic inference under heteroskedasticity of unknown form
• Extra-Binomial Variation in Logistic Linear Models
• Overdispersion: Models and estimation.
• A finite mixture distribution for modelling multinomial extra variation
• Negative binomial and mixed poisson regression
• Regression Analysis of Count Data
• The Touchard distribution
• The Gamma-count distribution in the analysis of experimental underdispersed data
• Multivariate statistical modelling based on generalized linear models.
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