Latent class and finite mixture models for multilevel data sets

DOI10.1177/0962280207081238zbMath1154.62086OpenAlexW2093895222WikidataQ31128264 ScholiaQ31128264MaRDI QIDQ3597443

Jeroen K. Vermunt

Publication date: 9 February 2009

Published in: Statistical Methods in Medical Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1177/0962280207081238

zbMATH Keywords

epilepsy dataintelligence testsprescription of antibiotics

Mathematics Subject Classification ID

Related Items (21)

A multilevel latent class analysis of the purchasing channels among European consumers ⋮ Model based clustering of customer choice data ⋮ A hierarchical modeling approach for clustering probability density functions ⋮ Model based clustering of high-dimensional binary data ⋮ Latent trajectory modelling of multivariate binary data ⋮ The spatial representation of consumer dispersion patterns via a new multi-level latent class methodology ⋮ A dimensionally reduced finite mixture model for multilevel data ⋮ Utility and application of SEM in delineating cause–effect relationship between ambient pollutant and fetal birth outcome ⋮ A two-step estimator for multilevel latent class analysis with covariates ⋮ Detecting intervention effects using a multilevel latent transition analysis with a mixture IRT model ⋮ Biomarker classification derived from finite growth mixture modeling with a time-varying covariate: an example with phosphorus and glomerular filtration rate ⋮ Clustering Discrete Choice Data ⋮ Long-term developments of respondent financial product portfolios in the EU: a multilevel latent class analysis ⋮ Multilevel Latent Class Models with Dirichlet Mixing Distribution ⋮ Dirichlet process mixture models for modeling and generating synthetic versions of nested categorical data ⋮ Model Selection for Complex Multilevel Latent Class Model ⋮ Finite mixture multilevel multidimensional ordinal IRT models for large scale cross-cultural research ⋮ Latent Variable Modelling: A Survey* ⋮ Solving genetic heterogeneity in extended families by identifying sub-types of complex diseases ⋮ Multilevel and latent variable modeling with composite links and exploded likelihoods ⋮ Finite mixture models for clustering multilevel data with multiple cluster structures

Uses Software

• Stata
• Mplus
• Latent GOLD

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Factor analysis for clustered observations
• Generalized multilevel structural equation modeling
• Some Covariance Models for Longitudinal Count Data with Overdispersion
• Dealing With Label Switching in Mixture Models
• A General Maximum Likelihood Analysis of Variance Components in Generalized Linear Models
• Exploratory latent structure analysis using both identifiable and unidentifiable models
• An EM algorithm for the estimation of parametric and nonparametric hierarchical nonlinear models
• A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains

This page was built for publication: Latent class and finite mixture models for multilevel data sets