A joint model for hierarchical continuous and zero-inflated overdispersed count data

DOI10.1080/00949655.2013.829058zbMath1457.62349OpenAlexW2052388553WikidataQ61786566 ScholiaQ61786566MaRDI QIDQ5220736

Wondwosen Kassahun, Christel Faes, Geert Verbeke, Thomas Neyens, Geert Molenberghs

Publication date: 27 March 2020

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

Full work available at URL: http://hdl.handle.net/1942/16621

zbMATH Keywords

clusteringoverdispersionjoint modelzero-inflationhurdle modelconjugate random effectnormal random effect

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12)

Related Items (7)

Analysis of mixed longitudinal (k,l)-Inflated power series, ordinal and continuous responses with sensitivity analysis to non-ignorable missing mechanism ⋮ Analysis of mixed correlated semi-continuous and β-inflated Poisson responses ⋮ Joint models for longitudinal zero-inflated overdispersed binomial and normal responses ⋮ A latent variable model for analyzing mixed longitudinal (k,l)-inflated count and ordinal responses ⋮ Marginal zero-inflated regression models for count data ⋮ Hierarchical models with normal and conjugate random effects : a review ⋮ Joint (k, l)-hurdle random effects models for mixed longitudinal power series and normal outcomes

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