Featured Publications
A meta-inference framework to integrate multiple external models into a current study.
Gu T, Taylor J, Mukherjee B. A meta-inference framework to integrate multiple external models into a current study. Biostatistics 2021, 24: 406-424. PMID: 34269371, PMCID: PMC10102901, DOI: 10.1093/biostatistics/kxab017.Peer-Reviewed Original ResearchConceptsAccuracy of statistical inferenceEmpirical Bayes estimatorsSummary-level informationBias-variance trade-offRelevant external informationBayes estimatorsStatistical inferenceExternal informationExternal estimatesNaive analysisNaive combinationInternational dataWeight estimationExternal modelMeta-analysis frameworkIndividual-level dataEfficiency gainsEstimationInfluence of informationTrade-offsInformationFramework
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