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 ResearchCausal Selection of Covariates in Regression Calibration for Mismeasured Continuous Exposure
Tang W, Spiegelman D, Liao X, Wang M. Causal Selection of Covariates in Regression Calibration for Mismeasured Continuous Exposure. Epidemiology 2024, 35: 320-328. PMID: 38630507, DOI: 10.1097/ede.0000000000001706.Peer-Reviewed Original ResearchConceptsMismeasured exposureOutcome modelRegression calibrationMeasurement error modelSelection of covariatesNonparametric settingEffect modificationCovariate adjustmentFiber intakeMeasurement errorCardiovascular diseaseEffects of fiber intakeStudy datasetOutcomesCovariatesComprehensive guidanceError modelRegressionHealthEfficiency lossErrorRosnerWillettExposureAdjustment
2022
Measurement errors in Gaussian mixture models using high-dimensional air pollution constituents data
Zhou X, Xu L, Fang J, Spiegelman D. Measurement errors in Gaussian mixture models using high-dimensional air pollution constituents data. ISEE Conference Abstracts 2022, 2022 DOI: 10.1289/isee.2022.o-sy-074.Peer-Reviewed Original Research
2021
Testing 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
EXPOSURE ASSESSMENT OF CONSTITUENTS OF AIR POLLUTION: A POOLED ANALYSIS OF NINE VALIDATION STUDIES
Kioumourtzoglou M, Spiegelman D, Hong B, Laden F, Williams R, Suh H. EXPOSURE ASSESSMENT OF CONSTITUENTS OF AIR POLLUTION: A POOLED ANALYSIS OF NINE VALIDATION STUDIES. ISEE Conference Abstracts 2011, 2011 DOI: 10.1289/isee.2011.00845.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
1997
Fully parametric and semi-parametric regression models for common events with covariate measurement error in main study/validation study designs.
Spiegelman D, Casella M. Fully parametric and semi-parametric regression models for common events with covariate measurement error in main study/validation study designs. Biometrics 1997, 53: 395-409. PMID: 9192443, DOI: 10.2307/2533945.Peer-Reviewed Original ResearchConceptsMain study/validation study designsSemi-parametric methodMeasurement error modelSemi-parametric estimatesCovariate measurement errorSemi-parametric regression modelEmpirical considerationsTrading efficiencyError modelInference proceedsConvenient mathematical propertiesMeasurement errorLikelihood functionModel choiceJoint likelihood functionValidation study designMisspecificationStandard theoryNonparametric formFamily of modelsImportant biasParametric resultsModel covariatesRegression modelsChoiceStatistical issues in assessing human population exposures
Weller E, Ryan L, Spiegelman D, Smith T. Statistical issues in assessing human population exposures. Chemometrics And Intelligent Laboratory Systems 1997, 37: 189-195. DOI: 10.1016/s0169-7439(97)00003-8.Peer-Reviewed Original ResearchDose-response relationshipStatistical issuesExposure-dose relationshipsMeasurement error problemsPrimary scientific interestHealth effectsStatistical aspectsStatistical methodsEnvironmental epidemiology studiesHealth outcomesEpidemiology studiesHuman population exposureExposure levelsMeasurement errorExposure assessmentError problemDirect applicationWelding fumesLoss of efficiencyExposureOutcomesPopulation exposureDose
1989
Correction of logistic regression relative risk estimates and confidence intervals for systematic within‐person measurement error
Rosner B, Willett WC, Spiegelman D. Correction of logistic regression relative risk estimates and confidence intervals for systematic within‐person measurement error. Statistics In Medicine 1989, 8: 1051-1069. PMID: 2799131, DOI: 10.1002/sim.4780080905.Peer-Reviewed Original ResearchConceptsLikelihood approximation methodApproximation methodLinear approximation methodSecond-order Taylor series expansionTaylor series expansionEstimation of lambdaMeasurement errorCoverage probabilitySeries expansionLikelihood estimationTrue odds ratioSimulation studyPerson measurement errorSystematic errorsRegression coefficientsErrorCoefficient betaCoefficient lambdaEstimationLogistic regression coefficientsLogistic functionEstimatesTrue exposure