Latent class analysis variable selection

From MaRDI portal
Publication:152163

DOI10.1007/s10463-009-0258-9zbMath1422.62085OpenAlexW1995986069WikidataQ34108017 ScholiaQ34108017MaRDI QIDQ152163

Nema Dean, Adrian E. Raftery, Adrian E. Raftery, Nema Dean

Publication date: 24 July 2009

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc2934856




Related Items (20)

Predictions based on the clustering of heterogeneous functions via shape and subject-specific covariatesVariable assessment in latent class modelsBayesian variable selection for latent class analysis using a collapsed Gibbs samplerFinding causative genes from high-dimensional data: an appraisal of statistical and machine learning approachesA hierarchical Bayesian approach for examining heterogeneity in choice decisionsItem selection by latent class-based methods: an application to nursing home evaluationMixture of latent trait analyzers for model-based clustering of categorical dataBayesian approaches to variable selection in mixture models with application to disease clusteringA model-based approach to simultaneous clustering and dimensional reduction of ordinal dataA tensor-EM method for large-scale latent class analysis with binary responsesBayesian inference for an unknown number of attributes in restricted latent class modelsAn exact method for partitioning dichotomous items within the framework of the monotone homogeneity modelAn Overview on the URV Model-Based Approach to Cluster Mixed-Type DataA macro-DAG structure based mixture modelVariable selection methods for model-based clusteringModel-based clustering based on sparse finite Gaussian mixturesLatent ignorability and item selection for nursing home case-mix evaluationGrowth mixture modeling with measurement selectionLCAvarselVariable selection for mixed data clustering: application in human population genomics


Uses Software


Cites Work


This page was built for publication: Latent class analysis variable selection