2023
A Note on Comparing the Bifactor and Second-Order Factor Models: Is the Bayesian Information Criterion a Routinely Dependable Index for Model Selection?
Raykov T, DiStefano C, Calvocoressi L. A Note on Comparing the Bifactor and Second-Order Factor Models: Is the Bayesian Information Criterion a Routinely Dependable Index for Model Selection? Educational And Psychological Measurement 2023, 84: 271-288. PMID: 38898876, PMCID: PMC11185100, DOI: 10.1177/00131644231166348.Peer-Reviewed Original Research
2009
Maximum-Likelihood Model Averaging To Profile Clustering of Site Types across Discrete Linear Sequences
Zhang Z, Townsend JP. Maximum-Likelihood Model Averaging To Profile Clustering of Site Types across Discrete Linear Sequences. PLOS Computational Biology 2009, 5: e1000421. PMID: 19557160, PMCID: PMC2695770, DOI: 10.1371/journal.pcbi.1000421.Peer-Reviewed Original ResearchConceptsInformation criterionModel averagingBayesian information criterionMaximum likelihood methodModel likelihoodModel uncertaintyModel selectionDescription of clustersLevel of clusteringPrecision of estimationAkaike information criterionParameter rangeCluster countsLikelihood methodComputational biologyCluster sizeGood accuracyConquer strategyAveragingClusteringModelHierarchical clusteringClustersStatisticsEstimationThe Bimodality Index: A criterion for Discovering and Ranking Bimodal Signatures from Cancer Gene Expression Profiling Data
Wang J, Wen S, Symmans WF, Pusztai L, Coombes KR. The Bimodality Index: A criterion for Discovering and Ranking Bimodal Signatures from Cancer Gene Expression Profiling Data. Cancer Informatics 2009, 7: cin.s2846. PMID: 19718451, PMCID: PMC2730180, DOI: 10.4137/cin.s2846.Peer-Reviewed Original Research
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