Random effects clustering in multilevel modeling: choosing a proper partition
DOI10.1007/s11634-018-0347-9zbMath1474.62012OpenAlexW2896072447MaRDI QIDQ2418095
Claudio Conversano, Massimo Cannas, Emiliano Sironi, Francesco Mola
Publication date: 3 June 2019
Published in: Advances in Data Analysis and Classification. ADAC (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11634-018-0347-9
model based clusteringBayesian nonparametriclabel switchinghierarchical modellingGini income inequality ratioGoodman and Kruskal predictability index
Classification and discrimination; cluster analysis (statistical aspects) (62H30) Bayesian problems; characterization of Bayes procedures (62C10) Generalized linear models (logistic models) (62J12) Empirical decision procedures; empirical Bayes procedures (62C12) Diagnostics, and linear inference and regression (62J20)
Uses Software
Cites Work
- Unnamed Item
- Optimal Bayesian estimators for latent variable cluster models
- Tree-Structured Clustering in Fixed Effects Models
- The two-parameter Poisson-Dirichlet distribution derived from a stable subordinator
- Bayesian cluster analysis: point estimation and credible balls (with discussion)
- Relabelling in Bayesian mixture models by pivotal units
- Bayesian effect fusion for categorical predictors
- Comparing clusterings -- an information based distance
- A Bayesian analysis of some nonparametric problems
- Clustering in linear-mixed models with a group fused lasso penalty
- Variation in caesarean delivery rates across hospitals: a Bayesian semi-parametric approach
- Measures of Association for Cross Classifications
- Modal clustering in a class of product partition models
- Improved criteria for clustering based on the posterior similarity matrix
- Modelling Clustered Heterogeneity: Fixed Effects, Random Effects and Mixtures
This page was built for publication: Random effects clustering in multilevel modeling: choosing a proper partition
