2019
Synthetic data method to incorporate external information into a current study
Gu T, Taylor J, Cheng W, Mukherjee B. Synthetic data method to incorporate external information into a current study. Canadian Journal Of Statistics 2019, 47: 580-603. PMID: 32773922, PMCID: PMC7410329, DOI: 10.1002/cjs.11513.Peer-Reviewed Original ResearchSynthetic data methodsDataset of sizeSynthetic data approachB modelMaximum likelihood estimation approachAsymptotic varianceGeneral regression contextSize nRegression contextSimulation studyVariable BEstimation approachDiverse scenariosCancer Prevention TrialExternal informationIndividual level dataDatasetProstate Cancer Prevention TrialPrevention trials
2018
Empirical Bayes Estimation and Prediction Using Summary-Level Information From External Big Data Sources Adjusting for Violations of Transportability
Estes J, Mukherjee B, Taylor J. Empirical Bayes Estimation and Prediction Using Summary-Level Information From External Big Data Sources Adjusting for Violations of Transportability. Statistics In Biosciences 2018, 10: 568-586. PMID: 31123532, PMCID: PMC6529204, DOI: 10.1007/s12561-018-9217-4.Peer-Reviewed Original ResearchEmpirical Bayes estimatorsSummary-level informationConstrained maximum likelihoodBayes estimatorsEmpirical Bayes shrinkage estimatorsSimulation studyBayes shrinkage estimatorShrinkage estimatorsLikelihood estimationCovariate distributionsConditional probability distributionData applicationsTrade biasMaximum likelihoodProbability distributionLoss of efficiencyCancer Prevention TrialIndividual-level dataEstimationProstate Cancer Prevention TrialPrevention trialsInternational population