Local influence diagnostics for hierarchical count data models with overdispersion and excess zeros

DOI10.1002/bimj.201500162zbMath1353.62125OpenAlexW2467914098WikidataQ31111273 ScholiaQ31111273MaRDI QIDQ2833475

Geert Molenberghs, Trias Wahyuni Rakhmawati, Christel Faes, Geert Verbeke

Publication date: 18 November 2016

Published in: Biometrical Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/bimj.201500162

zbMATH Keywords

overdispersionlocal influenceHurdle modelcombined modelzero-inflated modelexcess zerohierarchical count datalongitudinal clinical trialpatients with epileptic seizuresPoisson-normal model

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12) Diagnostics, and linear inference and regression (62J20)

Related Items

Sensitivity analysis of longitudinal count responses: a local influence approach and application to medical data ⋮ A new type 1 alpha power family of distributions and modeling data with correlation, overdispersion, and zero-inflation in the health data sets ⋮ A Bayesian approach to analyse overdispersed longitudinal count data ⋮ Negative variance components for non-negative hierarchical data with correlation, over-, and/or underdispersion ⋮ Influence diagnostics in mixed effects logistic regression models ⋮ Hierarchical models with normal and conjugate random effects : a review ⋮ Local influence diagnostics for hierarchical count data models with overdispersion and excess zeros ⋮ Bayesian model selection for longitudinal count data

Cites Work

• Unnamed Item
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• An extended random-effects approach to modeling repeated, overdispersed count data
• On estimation and influence diagnostics for zero-inflated negative binomial regression models
• A family of generalized linear models for repeated measures with normal and conjugate random effects
• Overdispersion: Models and estimation.
• The effect of misspecifying the random-effects distribution in linear mixed models for longitudinal data
• Models for discrete longitudinal data.
• The Combined Model: A Tool for Simulating Correlated Counts with Overdispersion
• Local influence diagnostics for hierarchical count data models with overdispersion and excess zeros
• Sensitivity Analysis for Nonrandom Dropout: A Local Influence Approach
• A Local Influence Approach Applied to Binary Data from a Psychiatric Study
• Multi-level zero-inflated Poisson regression modelling of correlated count data with excess zeros
• Diagnostics for Mixed-Model Analysis of Variance
• Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing
• Detection of Influential Observation in Linear Regression
• Influential Observations in Linear Regression
• Local Influence in Linear Mixed Models
• Zero‐Inflated Poisson and Binomial Regression with Random Effects: A Case Study
• 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
• Random effect models for repeated measures of zero-inflated count data