A Weibull-count approach for handling under- and overdispersed longitudinal/clustered data structures

DOI10.1177/1471082X18789992OpenAlexW2888894651MaRDI QIDQ5142259

Geert Molenberghs, Eduardo E. Jun. Ribeiro, Martial Luyts, Koen Matthijs, Geert Verbeke, Clarice Garcia Borges Demétrio, J. P. Hinde

Publication date: 30 December 2020

Published in: Statistical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1177/1471082x18789992

zbMATH Keywords

clusteringdispersionrandom effectslongitudinal profilesWeibull-count approach

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

Modelling Excess Zeros in Count Data: A New Perspective on Modelling Approaches

Uses Software

• COUNT

Cites Work

• A flexible regression model for count data
• A flexible zero-inflated model to address data dispersion
• Longitudinal data analysis using generalized linear models
• An extended random-effects approach to modeling repeated, overdispersed count data
• A compound class of Weibull and power series distributions
• A family of generalized linear models for repeated measures with normal and conjugate random effects
• Overdispersion: Models and estimation.
• Modelling heavy-tailed count data using a generalised Poisson-inverse Gaussian family
• Estimating negative variance components from Gaussian and non-Gaussian data: a mixed models approach
• Models for discrete longitudinal data.
• Negative Binomial Regression
• The Use of Score Tests for Inference on Variance Components
• Double Exponential Families and Their Use in Generalized Linear Regression
• Negative binomial and mixed poisson regression
• Approximate Inference in Generalized Linear Mixed Models
• A simple approach for the analysis of generalizea linear mixed models
• Generalized linear mixed models a pseudo-likelihood approach
• The Gamma-count distribution in the analysis of experimental underdispersed data
• Negative variance components for non-negative hierarchical data with correlation, over-, and/or underdispersion
• A note on a hierarchical interpretation for negative variance components
• A Useful Distribution for Fitting Discrete Data: Revival of the Conway–Maxwell–Poisson Distribution
• Conjugate analysis of the Conway-Maxwell-Poisson distribution
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