Mixtures of marginal models
From MaRDI portal
Publication:4506034
DOI10.1093/biomet/87.2.391zbMath0949.62067OpenAlexW2060986478MaRDI QIDQ4506034
Ori Rosen, Wenxin Jiang, Martin A. Tanner
Publication date: 2000
Published in: Biometrika (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1093/biomet/87.2.391
incomplete datamarginal modelsepileptic seizuresgeneralised estimating equationscorrelated outcome dataexpectation-solution algorithmiodine content data
Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12) Linear inference, regression (62J99)
Related Items (27)
Robust inference in the multilevel zero-inflated negative binomial model ⋮ GEE type inference for clustered zero-inflated negative binomial regression with application to dental caries ⋮ Grouped Generalized Estimating Equations for Longitudinal Data Analysis ⋮ Modified score function for monotone likelihood in the semiparametric mixture cure model ⋮ Analyzing longitudinal clustered count data with zero inflation: Marginal modeling using the Conway–Maxwell–Poisson distribution ⋮ GEE-based zero-inflated generalized Poisson model for clustered over or under-dispersed count data ⋮ Autoregressive mixture models for clustering time series ⋮ Multi-dimensional latent group structures with heterogeneous distributions ⋮ Heterogeneous analysis for clustered data using grouped finite mixture models ⋮ Unnamed Item ⋮ Generalized linear mixed models: a review and some extensions ⋮ Scalable and robust latent trajectory class analysis using artificial likelihood ⋮ Clustered Mixed Nonhomogeneous Poisson Process Spline Models for the Analysis of Recurrent Event Panel Data ⋮ Structural equation modeling of multivariate gamma density ⋮ Two-component mixtures of generalized linear mixed effects models for cluster correlated data ⋮ The large sample properties of the solutions of general estimating equations ⋮ The AU algorithm for estimating equations in the presence of missing data ⋮ Marginal regression models for clustered count data based on zero‐inflated Conway–Maxwell–Poisson distribution with applications ⋮ Multivariate Bernoulli Mixture Models with Application to Postmortem Tissue Studies in Schizophrenia ⋮ Multivariate Bernoulli Mixture Models with Application to Postmortem Tissue Studies in Schizophrenia ⋮ Marginal Projected Multivariate Linear Models for Clustered Angular Data ⋮ Marginal regression analysis of clustered failure time data with a cure fraction ⋮ Robust Estimation for Zero-Inflated Poisson Regression ⋮ Exploring the randomness of mentally generated head–tail sequences ⋮ Grouped Heterogeneous Mixture Modeling for Clustered Data ⋮ Latent mixture modeling for clustered data ⋮ Marginal models for zero inflated clustered data
This page was built for publication: Mixtures of marginal models
