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 ResearchMeSH KeywordsBiasComputer SimulationData Interpretation, StatisticalEnvironmental ExposureHumansLeast-Squares AnalysisLikelihood FunctionsLinear ModelsRegression AnalysisRisk FactorsTimeConceptsMeasurement 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 estimatesThe effect of risk factor misclassification on the partial population attributable risk
Wong BHW, Peskoe SB, Spiegelman D. The effect of risk factor misclassification on the partial population attributable risk. Statistics In Medicine 2018, 37: 1259-1275. PMID: 29333614, PMCID: PMC6003717, DOI: 10.1002/sim.7559.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAlcohol DrinkingBiasCausalityColorectal NeoplasmsConfounding Factors, EpidemiologicData Interpretation, StatisticalHumansMaleMiddle AgedMultivariate AnalysisRed MeatRisk FactorsUnited StatesConceptsPartial population attributable riskPopulation attributable riskRisk factorsAttributable riskRelative riskMultivariate-adjusted relative riskRed meatHealth Professionals FollowModifiable risk factorsLow folate intakeExposure of interestBackground risk factorsProfessionals FollowAlcohol intakeColorectal cancerFolate intakePublic health researchMultifactorial diseasePreventive interventionsPopulation-level impactJoint prevalenceHealth researchRiskIntakeExposure
2017
Evaluating Public Health Interventions: 6. Modeling Ratios or Differences? Let the Data Tell Us.
Spiegelman D, VanderWeele TJ. Evaluating Public Health Interventions: 6. Modeling Ratios or Differences? Let the Data Tell Us. American Journal Of Public Health 2017, 107: 1087-1091. PMID: 28590865, PMCID: PMC5463222, DOI: 10.2105/ajph.2017.303810.Peer-Reviewed Original Research
2005
Easy SAS Calculations for Risk or Prevalence Ratios and Differences
Spiegelman D, Hertzmark E. Easy SAS Calculations for Risk or Prevalence Ratios and Differences. American Journal Of Epidemiology 2005, 162: 199-200. PMID: 15987728, DOI: 10.1093/aje/kwi188.Peer-Reviewed Original ResearchBreast NeoplasmsData Interpretation, StatisticalEpidemiologic MeasurementsHumansPrevalenceRisk AssessmentSoftware
2002
Segmented Regression in the Presence of Covariate Measurement Error in Main Study/Validation Study Designs
Staudenmayer J, Spiegelman D. Segmented Regression in the Presence of Covariate Measurement Error in Main Study/Validation Study Designs. Biometrics 2002, 58: 871-877. PMID: 12495141, DOI: 10.1111/j.0006-341x.2002.00871.x.Peer-Reviewed Original Research
2000
Measurement error correction using validation data: a review of methods and their applicability in case-control studies
Thürigen D, Spiegelman D, Blettner M, Heuer C, Brenner H. Measurement error correction using validation data: a review of methods and their applicability in case-control studies. Statistical Methods In Medical Research 2000, 9: 447-474. PMID: 11191260, DOI: 10.1177/096228020000900504.Peer-Reviewed Original ResearchBiasCase-Control StudiesCohort StudiesData Interpretation, StatisticalModels, StatisticalReproducibility of ResultsResearch Design
1999
Matrix Methods for Estimating Odds Ratios with Misclassified Exposure Data: Extensions and Comparisons
Morrissey M, Spiegelman D. Matrix Methods for Estimating Odds Ratios with Misclassified Exposure Data: Extensions and Comparisons. Biometrics 1999, 55: 338-344. PMID: 11318185, DOI: 10.1111/j.0006-341x.1999.00338.x.Peer-Reviewed Original ResearchMeSH KeywordsAnti-Bacterial AgentsBiometryBreast NeoplasmsData Interpretation, StatisticalEpidemiologic MethodsFemaleHumansInfantLikelihood FunctionsModels, StatisticalOdds RatioPregnancySudden Infant DeathVitamin ADietary Fat and Coronary Heart Disease: A Comparison of Approaches for Adjusting for Total Energy Intake and Modeling Repeated Dietary Measurements
Hu F, Stampfer M, Rimm E, Ascherio A, Rosner B, Spiegelman D, Willett W. Dietary Fat and Coronary Heart Disease: A Comparison of Approaches for Adjusting for Total Energy Intake and Modeling Repeated Dietary Measurements. American Journal Of Epidemiology 1999, 149: 531-540. PMID: 10084242, DOI: 10.1093/oxfordjournals.aje.a009849.Peer-Reviewed Original ResearchMeSH KeywordsAdultCohort StudiesCoronary DiseaseData Interpretation, StatisticalDietary FatsEnergy IntakeFemaleFollow-Up StudiesHumansMaleMiddle AgedModels, StatisticalMyocardial InfarctionNutrition AssessmentRiskConceptsCoronary heart diseaseRisk of CHDTotal energy intakeNutrient density modelsBaseline dietHeart diseaseHigh intakeHealth StudyDietary measurementsEnergy intakeMultivariate nutrient density modelsPrevious cohort studiesNurses' Health StudyAssessment of dietEnergy adjustment methodCohort studyEnergy adjustmentFat intakeDietary fatRelative riskRecent dietDietary assessmentIntakeTrans fatsMultivariate model
1997
Measurement Error Correction for Logistic Regression Models with an “Alloyed Gold Standard”
Spiegelman D, Schneeweiss S, McDermott A. Measurement Error Correction for Logistic Regression Models with an “Alloyed Gold Standard”. American Journal Of Epidemiology 1997, 145: 184-196. PMID: 9006315, DOI: 10.1093/oxfordjournals.aje.a009089.Peer-Reviewed Original ResearchBiasData Interpretation, StatisticalHealth SurveysHumansLogistic ModelsNursesOdds RatioRegression Analysis