2019
Multi-view cluster analysis with incomplete data to understand treatment effects
Chao G, Sun J, Lu J, Wang AL, Langleben DD, Li CS, Bi J. Multi-view cluster analysis with incomplete data to understand treatment effects. Information Sciences 2019, 494: 278-293. PMID: 32863420, PMCID: PMC7455020, DOI: 10.1016/j.ins.2019.04.039.Peer-Reviewed Original ResearchCo-clustering methodsGranular computing methodData entryCo-clustering methodDifferent feature spacesIncomplete dataComputing methodFeature spaceData problemCluster validityIndicator matrixTime windowObserved entriesPrevious methodsEntire viewConsistent clustersDifferent viewsCommon scenarioMissing-data patternsAnalyticsAlgorithmEnhanced formulationCommon methodScenariosRecognition
2015
Data-Adaptive Shrinkage via the Hyperpenalized EM Algorithm
Boonstra P, Taylor J, Mukherjee B. Data-Adaptive Shrinkage via the Hyperpenalized EM Algorithm. Statistics In Biosciences 2015, 7: 417-431. PMID: 26834856, PMCID: PMC4728141, DOI: 10.1007/s12561-015-9132-x.Peer-Reviewed Original Research
2011
The use of complete-case and multiple imputation-based analyses in molecular epidemiology studies that assess interaction effects
Desai M, Esserman DA, Gammon MD, Terry MB. The use of complete-case and multiple imputation-based analyses in molecular epidemiology studies that assess interaction effects. Epidemiologic Perspectives & Innovations 2011, 8: 1-17. PMID: 21978450, PMCID: PMC3217865, DOI: 10.1186/1742-5573-8-5.Peer-Reviewed Original Research
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