2023
A Synthetic Data Integration Framework to Leverage External Summary-Level Information from Heterogeneous Populations
Gu T, Taylor J, Mukherjee B. A Synthetic Data Integration Framework to Leverage External Summary-Level Information from Heterogeneous Populations. Biometrics 2023, 79: 3831-3845. PMID: 36876883, PMCID: PMC10480346, DOI: 10.1111/biom.13852.Peer-Reviewed Original ResearchConceptsCovariate effectsStatistical inferenceHeterogeneity of covariate effectsRegression coefficient estimatesSummary-level informationImprove statistical inferenceInternational studiesOutcome YCovariate informationData integration frameworkStatistical efficiencyCoefficient estimatesPartial informationExternal populationGeneral frameworkIndividual-level dataRisk prediction modelExternal modelPrediction problemInternational study populationMultiple imputation
2013
Bayesian semiparametric analysis for two-phase studies of gene-environment interaction
Ahn J, Mukherjee B, Gruber S, Ghosh M. Bayesian semiparametric analysis for two-phase studies of gene-environment interaction. The Annals Of Applied Statistics 2013, 7: 543-569. PMID: 24587840, PMCID: PMC3935248, DOI: 10.1214/12-aoas599.Peer-Reviewed Original ResearchBayesian variable selection algorithmTwo-phase sampling designGene-environment independencePseudo-likelihood methodJoint effects of genotypeGene-environment interactionsHigh-dimensional modelsWeighted likelihoodCase-control study of colorectal cancerJoint distributionHierarchical priorsSemiparametric analysisRetrospective likelihoodGenetic markersCovariate informationLikelihood methodSimulation studyStudy of gene-environment interactionsStudy of colorectal cancerVariable selection algorithmBayesian approachPhase I dataSub-sample of casesBayesian methodsBayesian analysis