A robust Bayesian mixed effects approach for zero inflated and highly skewed longitudinal count data emanating from the zero inflated discrete Weibull distribution
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Publication:6627326
DOI10.1002/sim.8475zbMATH Open1546.62125MaRDI QIDQ6627326
R. Schall, Divan Aristo Burger, Johannes Theodorus Ferreira, Dinggeng Chen
Publication date: 29 October 2024
Published in: Statistics in Medicine (Search for Journal in Brave)
Cites Work
- A family of generalized linear models for repeated measures with normal and conjugate random effects
- Simple marginally noninformative prior distributions for covariance matrices
- Score tests for zero-inflated generalized Poisson mixed regression models
- A new robust regression model for proportions
- Some Covariance Models for Longitudinal Count Data with Overdispersion
- Sampling-Based Approaches to Calculating Marginal Densities
- Bayesian Modeling Using WinBUGS
- Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing
- Estimating Bayes Factors via Posterior Simulation With the Laplace-Metropolis Estimator
- Bayesian Measures of Model Complexity and Fit
- A novel Bayesian regression model for counts with an application to health data
- Generalized Poisson Distribution: the Property of Mixture of Poisson and Comparison with Negative Binomial Distribution
- A Weibull-count approach for handling under- and overdispersed longitudinal/clustered data structures
- Zero-inflated and overdispersed: what's one to do?
- Count Data Distributions
- A Useful Distribution for Fitting Discrete Data: Revival of the Conway–Maxwell–Poisson Distribution
- A default conjugate prior for variance components in generalized linear mixed models (Comment on article by Browne and Draper)
Related Items (2)
Zero-inflated modeling. II: Zero-inflated models for complex data structures ⋮ Nonlinear mixed-effects modeling of longitudinal count data: Bayesian inference about median counts based on the marginal zero-inflated discrete Weibull distribution
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