Analysis of zero-inflated clustered count data: a marginalized model approach
type: Item
instance of: scholarly article
title: Analysis of zero-inflated clustered count data: a marginalized model approach
zbMATH Open document ID: 1247.62108
author: Keunbaik Lee
author: Joon Jin Song
author: Dee Wood Harper
author: Yongsung Joo
published in: Computational Statistics and Data Analysis
publication date: 2012-09-15T00:00:00Z
Mathematics Subject Classification ID: 62G05
Mathematics Subject Classification ID: 65C60
zbMATH DE Number: 6083020
zbMATH Keywords: hurdle models
zbMATH Keywords: ZIP models
zbMATH Keywords: random effects
zbMATH Keywords: quasi-Newton
MaRDI profile type: Publication
full work available at URL: j.csda.2010.07.005
OpenAlex ID: W2049680061
cites work: Theory & Methods: Modelling Correlated Zero‐inflated Count Data
cites work: Trend in correlated proportions
cites work: Zero‐Inflated Poisson and Binomial Regression with Random Effects: A Case Study
cites work: Marginal models for zero inflated clustered data
cites work: Marginally Specified Logistic‐Normal Models for Longitudinal Binary Data
cites work: Misspecified maximum likelihood estimates and generalized linear mixed models
cites work: A Random-Effects Ordinal Regression Model for Multilevel Analysis
cites work: Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing
cites work: Likelihood-based approach for analysis of longitudinal nominal data using marginalized random effects models
cites work: Random effect models for repeated measures of zero-inflated count data
cites work: A Score Test for Testing a Zero‐Inflated Poisson Regression Model Against Zero‐Inflated Negative Binomial Alternatives
DOI: 10.1016/J.CSDA.2010.07.005
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description: scientific article; zbMATH DE number 6083020