2023
An inverse probability weighted regression method that accounts for right‐censoring for causal inference with multiple treatments and a binary outcome
Yu Y, Zhang M, Mukherjee B. An inverse probability weighted regression method that accounts for right‐censoring for causal inference with multiple treatments and a binary outcome. Statistics In Medicine 2023, 42: 3699-3715. PMID: 37392070, DOI: 10.1002/sim.9826.Peer-Reviewed Original ResearchMeSH KeywordsComputer SimulationHumansMaleModels, StatisticalProbabilityPropensity ScoreProstatic NeoplasmsRegression AnalysisTreatment OutcomeConceptsRight censoringWeighted score functionCausal treatment effectsAverage treatment effectAsymptotic propertiesCensored componentPre-specified time windowEstimation consistencyRobustness propertiesSimulation studyBinary outcomesPresence of confoundersCensoringScoring functionInverse probabilityTreatment effectsEstimationSources of biasInferenceLetter CComparative effectiveness researchTreatment switchRegression methodLogistic regression modelsInsurance claims database
2019
Urinary concentrations of phenols in association with biomarkers of oxidative stress in pregnancy: Assessment of effects independent of phthalates
Ferguson K, Lan Z, Yu Y, Mukherjee B, McElrath T, Meeker J. Urinary concentrations of phenols in association with biomarkers of oxidative stress in pregnancy: Assessment of effects independent of phthalates. Environment International 2019, 131: 104903. PMID: 31288179, PMCID: PMC6728185, DOI: 10.1016/j.envint.2019.104903.Peer-Reviewed Original ResearchConceptsUrinary phthalate metabolitesOxidative stress biomarkersNon-null associationsPhthalate metabolitesBiomarkers of oxidative stressInterquartile rangeBenzophenone-3Associated with increasesOutcome biomarkersIncreased maternal oxidative stressStress biomarkersExposure to environmental phenolsOxidative stressReduced fetal growthUrinary oxidative stress biomarkersMaternal oxidative stressEffect estimatesAdaptive elastic net modelStudy populationPreterm birthFetal growthConcentration of phenolUrinary phenolPregnancyUrinary concentrations
2018
Improving 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 ResearchMeSH KeywordsBayes TheoremData Interpretation, StatisticalHumansLinear ModelsModels, StatisticalRegression AnalysisConceptsOutcome 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
2017
Complete hazard ranking to analyze right-censored data: An ALS survival study
Huang Z, Zhang H, Boss J, Goutman S, Mukherjee B, Dinov I, Guan Y, . Complete hazard ranking to analyze right-censored data: An ALS survival study. PLOS Computational Biology 2017, 13: e1005887. PMID: 29253881, PMCID: PMC5749893, DOI: 10.1371/journal.pcbi.1005887.Peer-Reviewed Original ResearchRobust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence
Liu G, Mukherjee B, Lee S, Lee AW, Wu AH, Bandera EV, Jensen A, Rossing MA, Moysich KB, Chang-Claude J, Doherty JA, Gentry-Maharaj A, Kiemeney L, Gayther SA, Modugno F, Massuger L, Goode EL, Fridley BL, Terry KL, Cramer DW, Ramus SJ, Anton-Culver H, Ziogas A, Tyrer JP, Schildkraut JM, Kjaer SK, Webb PM, Ness RB, Menon U, Berchuck A, Pharoah PD, Risch H, Pearce CL, Consortium F. Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence. American Journal Of Epidemiology 2017, 187: 366-377. PMID: 28633381, PMCID: PMC5860584, DOI: 10.1093/aje/kwx243.Peer-Reviewed Original Research
2016
Classification and Clustering Methods for Multiple Environmental Factors in Gene–Environment Interaction
Ko Y, Mukherjee B, Smith J, Kardia S, Allison M, Roux A. Classification and Clustering Methods for Multiple Environmental Factors in Gene–Environment Interaction. Epidemiology 2016, 27: 870-878. PMID: 27479650, PMCID: PMC5039086, DOI: 10.1097/ede.0000000000000548.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overAtherosclerosisBayes TheoremCluster AnalysisData Interpretation, StatisticalEnvironmental ExposureEpidemiologic Research DesignFemaleFollow-Up StudiesGene-Environment InteractionGenetic Predisposition to DiseaseHumansMiddle AgedModels, StatisticalRegression AnalysisRisk FactorsConceptsMultiple environmental exposuresGene-environment interactionsG x EEnvironmental exposuresMultiethnic Study of AtherosclerosisStudy of AtherosclerosisGene-environmentEffect modificationMultiethnic StudyEnvironmental factorsExposure subgroupsEnvironmental exposure profilesMain effectExposure profilesE studyEfficient analysis strategyE analysisMultiple environmental factorsSubgroupsAnalysis strategyFactorsExposureProduct termsOn-time Measles and Pneumococcal Vaccination of Shanghai Children
Wagner A, Sun X, Huang Z, Ren J, Mukherjee B, Wells E, Boulton M. On-time Measles and Pneumococcal Vaccination of Shanghai Children. The Pediatric Infectious Disease Journal 2016, 35: e311-e317. PMID: 27294307, DOI: 10.1097/inf.0000000000001267.Peer-Reviewed Original ResearchConceptsPneumococcal conjugate vaccinePneumococcal conjugate vaccine administrationMeasles-containing vaccineMonths of ageShanghai Immunization Program Information SystemProportion of infant deathsShanghai childrenComparator vaccineDose 2Logistic regression modelsConjugate vaccineDose 1Pneumococcal vaccineImmunization scheduleVaccination outcomesInfant deathsPediatric immunization scheduleVaccineMonthsDisease control effortsLate vaccinationOddsAdministrationChina censusVaccination levels
2015
Association between Stress Response Genes and Features of Diurnal Cortisol Curves in the Multi-Ethnic Study of Atherosclerosis: A New Multi-Phenotype Approach for Gene-Based Association Tests
He Z, Payne E, Mukherjee B, Lee S, Smith J, Ware E, Sánchez B, Seeman T, Kardia S, Roux A. Association between Stress Response Genes and Features of Diurnal Cortisol Curves in the Multi-Ethnic Study of Atherosclerosis: A New Multi-Phenotype Approach for Gene-Based Association Tests. PLOS ONE 2015, 10: e0126637. PMID: 25993632, PMCID: PMC4439141, DOI: 10.1371/journal.pone.0126637.Peer-Reviewed Original ResearchConceptsMulti-Ethnic Study of AtherosclerosisMarker association testsCortisol featuresMulti-Ethnic StudySingle marker association testsStudy of AtherosclerosisAssociation TestGene level association testsGene-based association testsEthnic-specific resultsMeta-analysisGenetic contribution to variabilityGene-level analysisStress-responsive genesSample of European AmericansGenotype-phenotype associationsDiurnal cortisol curveHispanic AmericansChronic diseasesMultiple physiological systemsDaily cortisol profilesAfrican AmericansGene approachGene-basedMultiple testing
2013
Novel Likelihood Ratio Tests for Screening Gene‐Gene and Gene‐Environment Interactions With Unbalanced Repeated‐Measures Data
Ko Y, Saha‐Chaudhuri P, Park S, Vokonas P, Mukherjee B. Novel Likelihood Ratio Tests for Screening Gene‐Gene and Gene‐Environment Interactions With Unbalanced Repeated‐Measures Data. Genetic Epidemiology 2013, 37: 581-591. PMID: 23798480, PMCID: PMC4009698, DOI: 10.1002/gepi.21744.Peer-Reviewed Original ResearchConceptsGene-environment interactionsGene-gene interactionsTesting gene-gene interactionsModel gene-gene interactionsRepeated-measures studyLongitudinal cohort studyNormative Aging StudyCumulative lead exposureCase-control studyGene-environmentGene-geneType I error rateCohort studyScreening toolAging StudyLikelihood ratio testMain effectEpistasis patternsRatio testLead exposureHemochromatosis genePower propertiesPulse pressureRegression-based approachRestrictive assumptions
2012
Incorporating auxiliary information for improved prediction in high-dimensional datasets: an ensemble of shrinkage approaches
Boonstra P, Taylor J, Mukherjee B. Incorporating auxiliary information for improved prediction in high-dimensional datasets: an ensemble of shrinkage approaches. Biostatistics 2012, 14: 259-272. PMID: 23087411, PMCID: PMC3590922, DOI: 10.1093/biostatistics/kxs036.Peer-Reviewed Original ResearchConceptsHigh-dimensional datasetsAuxiliary informationRidge estimatorBayesian alternativeOutcome YSimulation studyEstimates of BShrinkage approachBiological processesRidge regressionGene expression datasetsDatasetGenomic technologiesMicroarray technologyOptimal choiceBalance efficiencyX.EstimationPrediction errorPolymerase chain reactionBiological phenomenaInformationTechnologyQuantitative real-time polymerase chain reactionWhere science meets policy: comparing longitudinal and cross-sectional designs to address diarrhoeal disease burden in the developing world
Markovitz A, Goldstick J, Levy K, Cevallos W, Mukherjee B, Trostle J, Eisenberg J. Where science meets policy: comparing longitudinal and cross-sectional designs to address diarrhoeal disease burden in the developing world. International Journal Of Epidemiology 2012, 41: 504-513. PMID: 22253314, PMCID: PMC3324455, DOI: 10.1093/ije/dyr194.Peer-Reviewed Original ResearchConceptsCross-sectional studyCross-sectional designEffect estimatesLongitudinal studyRisk factorsDisease risk factorsRisk factor distributionInforming public health policyPublic health policiesPublic health communityRisk factor effectsHousehold risk factorsDiarrhoeal disease burdenFactor effect estimatesHealth policyDiarrhoeal disease surveillanceEcuadorian villageNational policy decisionsHealth communityDisease burdenCross-sectionDisease surveillanceFactor distributionRiskGeographic regions
2010
A review of statistical methods for testing genetic anticipation: looking for an answer in Lynch syndrome
Boonstra P, Gruber S, Raymond V, Huang S, Timshel S, Nilbert M, Mukherjee B. A review of statistical methods for testing genetic anticipation: looking for an answer in Lynch syndrome. Genetic Epidemiology 2010, 34: 756-768. PMID: 20878717, PMCID: PMC3894615, DOI: 10.1002/gepi.20534.Peer-Reviewed Original ResearchConceptsAffected parent-child pairsDanish HNPCC registerParent-child pairsLynch syndromePaired t-testGenetic anticipationLynch syndrome cohortCancer genetics clinicsT-testEvidence of genetic anticipationFamily membersClinic-based populationRandom-effects modelGenetics clinicAffected pairsMismatch repairUnaffected family membersFamilial correlationsAffected parentType I errorSyndrome cohortRegression modelsPedigree dataDecreasing ageAscertainmentMissing Exposure Data in Stereotype Regression Model: Application to Matched Case–Control Study with Disease Subclassification
Ahn J, Mukherjee B, Gruber S, Sinha S. Missing Exposure Data in Stereotype Regression Model: Application to Matched Case–Control Study with Disease Subclassification. Biometrics 2010, 67: 546-558. PMID: 20560931, PMCID: PMC3119773, DOI: 10.1111/j.1541-0420.2010.01453.x.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsBayes TheoremBiometryCase-Control StudiesClassificationColorectal NeoplasmsComputer SimulationHumansRegression AnalysisConceptsStereotype regression modelSubtypes of casesDeletion of observationsExpectation/conditional maximization algorithmBaseline category logit modelEstimation of model parametersMissingness mechanismData mechanismCase-control dataProportional oddsBayesian approachCategorical responsesCase-control studyCase-control study of colorectal cancerMissingnessMaximization algorithmCategorical outcomesMonte CarloModel assumptionsRegression modelsStudy of colorectal cancerModel parametersNonidentifiabilityDisease subclassificationMultinomial logit model
2009
Bone Lead Level Prediction Models and Their Application to Examine the Relationship of Lead Exposure and Hypertension in the Third National Health and Nutrition Examination Survey
Park S, Mukherjee B, Xia X, Sparrow D, Weisskopf M, Nie H, Hu H. Bone Lead Level Prediction Models and Their Application to Examine the Relationship of Lead Exposure and Hypertension in the Third National Health and Nutrition Examination Survey. Journal Of Occupational And Environmental Medicine 2009, 51: 1422-1436. PMID: 19952788, PMCID: PMC2939477, DOI: 10.1097/jom.0b013e3181bf6c8d.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overBone and BonesBostonCohort StudiesEnvironmental ExposureFemaleHumansHypertensionLeadLongitudinal StudiesMaleMiddle AgedNutrition SurveysPatellaRadiographyRegression AnalysisRisk AssessmentRisk FactorsSpectrometry, X-Ray EmissionTibiaUnited StatesUnited States Department of Veterans AffairsYoung AdultConceptsNational Health and Nutrition Examination SurveyThird National Health and Nutrition Examination SurveyHealth and Nutrition Examination SurveyNutrition Examination SurveyCommunity-based cohortPatella leadExamination SurveyCohort of older menCommunity-based cohort of older menK X-ray fluorescenceNHANES-IIISignificant associationBlood lead levelsOlder menStandard covariatesPatellaExternal validationCorrelation coefficientBlood leadLead exposureTibiaLead levelsAssociationSurveyLead studiesBayesian inference for the stereotype regression model: Application to a case–control study of prostate cancer
Ahn J, Mukherjee B, Banerjee M, Cooney K. Bayesian inference for the stereotype regression model: Application to a case–control study of prostate cancer. Statistics In Medicine 2009, 28: 3139-3157. PMID: 19731262, PMCID: PMC3103066, DOI: 10.1002/sim.3693.Peer-Reviewed Original ResearchMeSH KeywordsAdultBayes TheoremCase-Control StudiesHumansMaleMiddle AgedNeoplasm StagingProstatic NeoplasmsRegression AnalysisConceptsStereotype regression modelProportional odds modelLog-odds-ratioStereotype modelMaximum likelihood estimationOdds modelBayesian inferenceAdjacent category logit modelCase-control study of prostate cancerLack of identifiabilityModel comparison procedureLikelihood estimationProduct representationValid inferenceFrequentist approachUnordered outcomesCategorical responsesOrdered outcomesCategory-specific scoresOdd structuresComparison procedureCategorical outcomesLatent variablesInferenceCase-control study