GEE-based zero-inflated generalized Poisson model for clustered over or under-dispersed count data

DOI10.1080/00949655.2019.1632857OpenAlexW2954595562WikidataQ127624775 ScholiaQ127624775MaRDI QIDQ5107485

Abbas Moghimbeigi, Hossein Mahjub, Fatemeh Sarvi

Publication date: 27 April 2020

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

Full work available at URL: https://doi.org/10.1080/00949655.2019.1632857

zbMATH Keywords

dispersiongeneralized estimating equationzero-inflationgeneralized Poisson regressionexpectation-solution algorithm

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

Unit gamma regression models for correlated bounded data

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• GEE type inference for clustered zero-inflated negative binomial regression with application to dental caries
• The exact bootstrap method shown on the example of the mean and variance estimation
• A score test for extra zeros in negative binomial mixed models
• A Score Test for Testing a Zero‐Inflated Poisson Regression Model Against Zero‐Inflated Negative Binomial Alternatives
• Multilevel zero-inflated negative binomial regression modeling for over-dispersed count data with extra zeros
• Regression Analysis of Poisson-Distributed Data
• Marginal models for zero inflated clustered data
• Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing
• Zero-inflated proportion data models applied to a biological control assay
• Mixtures of marginal models
• Theory & Methods: Modelling Correlated Zero‐inflated Count Data
• Zero‐Inflated Poisson and Binomial Regression with Random Effects: A Case Study
• Zero-inflated generalized Poisson models with regression effects on the mean, dispersion and zero-inflation level applied to patent outsourcing rates
• Analyzing clustered count data with a cluster-specific random effect zero-inflated Conway–Maxwell–Poisson distribution
• Generalized Poisson Distribution: the Property of Mixture of Poisson and Comparison with Negative Binomial Distribution
• Marginal regression models for clustered count data based on zero‐inflated Conway–Maxwell–Poisson distribution with applications
• Longitudinal Data Analysis
• The S-U algorithm for missing data problems

This page was built for publication: GEE-based zero-inflated generalized Poisson model for clustered over or under-dispersed count data