Featured Publications
A framework for understanding selection bias in real-world healthcare data
Kundu R, Shi X, Morrison J, Barrett J, Mukherjee B. A framework for understanding selection bias in real-world healthcare data. Journal Of The Royal Statistical Society Series A (Statistics In Society) 2024, 187: 606-635. PMID: 39281782, PMCID: PMC11393555, DOI: 10.1093/jrsssa/qnae039.Peer-Reviewed Original ResearchElectronic health recordsSelection biasAssociation of cancerMultiple sources of biasHealth recordsHealthcare systemSources of biasReal-world healthcare dataBinary outcomesEstimation of associated parametersHealthcare dataReal-world dataPotential biasSample sizeStandard errorData exampleVariance formulaAnalysis of real-world dataAssociationSimulation studyWeighting approachBiological sexAssociated parametersBiasMultiple sources
2018
Informing a Risk Prediction Model for Binary Outcomes with External Coefficient Information
Cheng W, Taylor J, Gu T, Tomlins S, Mukherjee B. Informing a Risk Prediction Model for Binary Outcomes with External Coefficient Information. Journal Of The Royal Statistical Society Series C (Applied Statistics) 2018, 68: 121-139. PMID: 31105344, PMCID: PMC6519970, DOI: 10.1111/rssc.12306.Peer-Reviewed Original ResearchOutcome variable YEfficiency of estimationMeasurement error literatureDistribution of B.Regression coefficientsVariable YRegression modelsBinary outcomesVariable BLogistic regression modelsRisk prediction modelAlternative expressionBinary BImproved estimatesGaussian distributionProstate Cancer Prevention Trial Risk CalculatorProstate cancer antigen 3Risk calculatorStandard errorEstimationPredictive powerAntigen 3RegressionHistorical dataImproving estimation and prediction in linear regression incorporating external information from an established reduced model
Cheng W, Taylor J, Vokonas P, Park S, Mukherjee B. Improving estimation and prediction in linear regression incorporating external information from an established reduced model. Statistics In Medicine 2018, 37: 1515-1530. PMID: 29365342, PMCID: PMC5889759, DOI: 10.1002/sim.7600.Peer-Reviewed Original ResearchConceptsOutcome variable YEfficiency of estimationApproximate Bayesian inferenceBayes solutionVariable YNonlinear constraintsInferential frameworkVariable BE(Y|XImprove inferenceBayesian inferenceEffective computational methodParameter spaceReduced modelImproved estimatesLinear regression modelsTransformation approachStandard errorDunsonInferenceEstimationRegression modelsProblemCovariatesSpace