2022
Variable Selection with Multiply-Imputed Datasets: Choosing Between Stacked and Grouped Methods
Du J, Boss J, Han P, Beesley L, Kleinsasser M, Goutman S, Batterman S, Feldman E, Mukherjee B. Variable Selection with Multiply-Imputed Datasets: Choosing Between Stacked and Grouped Methods. Journal Of Computational And Graphical Statistics 2022, 31: 1063-1075. PMID: 36644406, PMCID: PMC9838615, DOI: 10.1080/10618600.2022.2035739.Peer-Reviewed Original ResearchVariable selectionSimultaneous coefficient estimationPenalized regression methodsBinary outcome dataObjective functionR-package <i>Shrinkage penaltyGeneral classCyclic coordinate descentVariable selection algorithmCoefficient estimatesSupplementary materialsMethod to dataCoordinate descentMultiple imputationALS riskMultiply-imputedOutcome dataFunction formulationSelectivity propertiesSelection algorithmEstimationOptimization algorithmMissingnessBiomedical applications
2019
Estimating Outcome-Exposure Associations when Exposure Biomarker Detection Limits vary Across Batches.
Boss J, Mukherjee B, Ferguson K, Aker A, Alshawabkeh A, Cordero J, Meeker J, Kim S. Estimating Outcome-Exposure Associations when Exposure Biomarker Detection Limits vary Across Batches. Epidemiology 2019, 30: 746-755. PMID: 31299670, PMCID: PMC6677587, DOI: 10.1097/ede.0000000000001052.Peer-Reviewed Original ResearchConceptsBinary outcome dataLikelihood-based methodsComplete-case analysisDistributional assumptionsAssignment of samplesSuperior estimation propertiesSimulation studyComplete-caseMultiple imputation strategyExposure dataMultiple batchesBatch assignmentEstimated propertiesLimit-variablesSingle imputationMultiple imputationCohort study