2024
Exposure measurement error in air pollution health effect studies: A pooled analysis of personal exposure validation studies across the US
Zhang B, Eum K, Szpiro A, Zhang N, Hernández Ramírez R, Spiegelman D, Suh H. Exposure measurement error in air pollution health effect studies: A pooled analysis of personal exposure validation studies across the US. ISEE Conference Abstracts 2024, 2024 DOI: 10.1289/isee.2024.0981.Peer-Reviewed Original Research
2023
Estimation and inference for exposure effects with latency in the Cox proportional hazards model in the presence of exposure measurement error
Peskoe S, Zhang N, Spiegelman D, Wang M. Estimation and inference for exposure effects with latency in the Cox proportional hazards model in the presence of exposure measurement error. The Annals Of Applied Statistics 2023, 17 DOI: 10.1214/22-aoas1682.Peer-Reviewed Original ResearchMediation analysis in the presence of continuous exposure measurement error
Cheng C, Spiegelman D, Li F. Mediation analysis in the presence of continuous exposure measurement error. Statistics In Medicine 2023, 42: 1669-1686. PMID: 36869626, PMCID: PMC11320713, DOI: 10.1002/sim.9693.Peer-Reviewed Original ResearchConceptsBody mass indexExposure measurement errorPhysical activityMediation proportionHealth Professionals FollowCardiovascular disease incidenceProfessionals FollowMediation analysisMass indexCardiovascular diseaseLower riskStudy designEffect estimatesValidation study designContinuous exposureBiased effect estimatesTrue exposureMediatorsExposureValidation studyBinary outcomesHealth science studiesOutcomesRiskDisease incidence
2021
A Bayesian approach for estimating the partial potential impact fraction with exposure measurement error under a main study/internal validation design
Chen X, Chang J, Spiegelman D, Li F. A Bayesian approach for estimating the partial potential impact fraction with exposure measurement error under a main study/internal validation design. Statistical Methods In Medical Research 2021, 31: 404-418. PMID: 34841964, DOI: 10.1177/09622802211060514.Peer-Reviewed Original ResearchConceptsPotential impact fractionImpact fractionExposure measurement errorHealth professionalsStudy designColorectal cancer incidenceValidation study designBurden of diseaseRisk factorsCancer incidenceHealth StudyDisease casesPublic health studiesRed meatContinuous exposureExposureProfessionalsIncidenceReclassification approachValidation designDiseaseIntakeTesting gene–environment interactions in the presence of confounders and mismeasured environmental exposures
Cheng C, Spiegelman D, Wang Z, Wang M. Testing gene–environment interactions in the presence of confounders and mismeasured environmental exposures. G3: Genes, Genomes, Genetics 2021, 11: jkab236. PMID: 34568916, PMCID: PMC8473983, DOI: 10.1093/g3journal/jkab236.Peer-Reviewed Original ResearchConceptsStandard logistic regression approachGreater statistical powerStatistical powerBinary disease outcomeComputational efficiencyIllustrative exampleComputation timeExtensive simulation experimentsMost simulation scenariosMeasurement errorRegression approachConsideration adjustmentsSimulation experimentsExposure measurement errorReverse testLogistic regression approachSimulation scenariosLinear discriminant analysisApproachReverse approachPowerErrorDiscriminant analysis
2018
There is no impact of exposure measurement error on latency estimation in linear models
Peskoe SB, Spiegelman D, Wang M. There is no impact of exposure measurement error on latency estimation in linear models. Statistics In Medicine 2018, 38: 1245-1261. PMID: 30515870, PMCID: PMC6542365, DOI: 10.1002/sim.8038.Peer-Reviewed Original ResearchConceptsMeasurement error modelLinear measurement error modelsLeast squares estimatorStandard measurement error modelLinear modelError modelRegression coefficient estimatesLikelihood-based methodsMeasurement errorExposure measurement errorSquares estimatorWide classGeneralized linear modelMean functionStatistical modelCovariance structureError settingsNaive estimatorBody mass indexBehavioral risk factorsLatency parametersExposure-disease relationshipsPrimary disease modelTime-varying exposureCoefficient estimates
2011
AN APPLICATION OF A RISK SET CALIBRATION METHOD TO A STUDY OF AIR POLLUTION EFFECTS ON ALL CAUSE MORTALITY IN THE NURSES’ HEALTH STUDY
Liao X, Spiegelman D, Hart J, Hong B, Puett R, Suh H, Laden F. AN APPLICATION OF A RISK SET CALIBRATION METHOD TO A STUDY OF AIR POLLUTION EFFECTS ON ALL CAUSE MORTALITY IN THE NURSES’ HEALTH STUDY. ISEE Conference Abstracts 2011, 2011 DOI: 10.1289/isee.2011.00990.Peer-Reviewed Original ResearchCause mortalityRelative riskHealth StudyChronic exposureChronic PM2.5 exposureNurses' Health StudyIndividual exposure levelsAverage of PM2.5Risk factorsExposure measurement errorState of residenceEstimates of riskParticipants' residencesPM2.5 exposureHealth outcomesMortalityMonthly exposureExposure levelsPersonal exposureExposure monitoringRiskCalendar yearAir pollution effectsExposureMidwestern metropolitan area
2007
Regression calibration for logistic regression with multiple surrogates for one exposure
Weller E, Milton D, Eisen E, Spiegelman D. Regression calibration for logistic regression with multiple surrogates for one exposure. Journal Of Statistical Planning And Inference 2007, 137: 449-461. DOI: 10.1016/j.jspi.2006.01.009.Peer-Reviewed Original ResearchCross-sectional epidemiologic studyExposure measurementsExposure-response associationsQuantitative exposure measurementsLung functionBaseline prevalenceExposure measurement errorOccupational exposureEpidemiologic studiesFluid exposureHealth outcomesExposure assessment studiesLogistic regressionIndividual exposurePersonal monitors
2006
Methods to Adjust for Bias in Effect Estimates Due to Exposure Measurement Error in Environmental and Occupational Studies
Spiegelman D. Methods to Adjust for Bias in Effect Estimates Due to Exposure Measurement Error in Environmental and Occupational Studies. American Journal Of Epidemiology 2006, 163: s154-s154. DOI: 10.1093/aje/163.suppl_11.s154-d.Peer-Reviewed Original Research
1998
Correcting for bias in relative risk estimates due to exposure measurement error: a case study of occupational exposure to antineoplastics in pharmacists.
Spiegelman D, Valanis B. Correcting for bias in relative risk estimates due to exposure measurement error: a case study of occupational exposure to antineoplastics in pharmacists. American Journal Of Public Health 1998, 88: 406-12. PMID: 9518972, PMCID: PMC1508329, DOI: 10.2105/ajph.88.3.406.Peer-Reviewed Original ResearchConceptsMeasurement error modelInterval estimatesExposure measurement errorMeasurement errorError modelPrevalence ratiosRelative riskLikelihood-based methodsLog relative riskNondifferential measurement errorStatistical methodsRelative risk estimatesOutcomes of interestOccupational exposurePublic health researchHospital pharmacistsLogistic regressionRisk estimatesWeekly numberFirst methodHealth effectsUsual pointHealth researchErrorPharmacists