Finite mixture regression model with random effects: application to neonatal hospital length of stay

DOI10.1016/S0167-9473(02)00180-9zbMath1256.62065MaRDI QIDQ951795

Angus S. K. Ng, Andy H. Lee, Kelvin. K. W. Yau

Publication date: 4 November 2008

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

zbMATH Keywords

EM algorithmheterogeneitymixture distributionsgeneralised linear mixed models

Mathematics Subject Classification ID

Related Items (9)

Comparison of the EM, CEM and SEM algorithms in the estimation of finite mixtures of linear mixed models: a simulation study ⋮ Estimation of a semiparametric mixture of regressions model ⋮ Missing data imputation through GTM as a mixture of \(t\)-distributions ⋮ Extending finite mixtures of \(t\) linear mixed-effects models with concomitant covariates ⋮ Two-stage hierarchical modeling for analysis of subpopulations in conditional distributions ⋮ Mixtures of regressions with predictor-dependent mixing proportions ⋮ Mixture of linear mixed models using multivariatetdistribution ⋮ A panel data model of length of stay in hospitals for hip replacements ⋮ Simultaneous fixed and random effects selection in finite mixture of linear mixed-effects models

Cites Work

• Fast EM-type Implementations for Mixed Effects Models
• Finite Mixture Models with Concomitant Information: Assessing Diagnostic Criteria for Diabetes
• The derivation of blup, ML, REML estimation methods for generalised linear mixed models
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