2020
Estimation and inference for the population attributable risk in the presence of misclassification
Wong BHW, Lee J, Spiegelman D, Wang M. Estimation and inference for the population attributable risk in the presence of misclassification. Biostatistics 2020, 22: 805-818. PMID: 32112073, PMCID: PMC8966954, DOI: 10.1093/biostatistics/kxz067.Peer-Reviewed Original ResearchConceptsPopulation attributable riskAttributable riskPartial population attributable riskHigh red meat intakeColorectal cancer incidenceRed meat intakeAlcohol intakeRisk factorsCancer incidenceMeat intakeEpidemiologic studiesPublic health researchDisease casesStudy designValidation study designInternal validation studyHealth researchTarget populationIntakeValidation studyRiskHealth evaluation methodPresence of misclassificationIncidenceDisease
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
2017
Prevalence estimation when disease status is verified only among test positives: Applications in HIV screening programs
Thomas E, Peskoe S, Spiegelman D. Prevalence estimation when disease status is verified only among test positives: Applications in HIV screening programs. Statistics In Medicine 2017, 37: 1101-1114. PMID: 29230839, PMCID: PMC6512805, DOI: 10.1002/sim.7568.Peer-Reviewed Original Research
2004
Estimating treatment effects in studies of perinatal transmission of HIV
Bang H, Spiegelman D. Estimating treatment effects in studies of perinatal transmission of HIV. Biostatistics 2004, 5: 31-43. PMID: 14744826, DOI: 10.1093/biostatistics/5.1.31.Peer-Reviewed Original Research
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
Efficient regression calibration for logistic regression in main study/internal validation study designs with an imperfect reference instrument
Spiegelman D, Carroll R, Kipnis V. Efficient regression calibration for logistic regression in main study/internal validation study designs with an imperfect reference instrument. Statistics In Medicine 2000, 20: 139-160. PMID: 11135353, DOI: 10.1002/1097-0258(20010115)20:1<139::aid-sim644>3.0.co;2-k.Peer-Reviewed Original Research
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 Research
1998
Vitamins A, C and E and the risk of breast cancer: results from a case-control study in Greece
Bohlke K, Spiegelman D, Trichopoulou A, Katsouyanni K, Trichopoulos D. Vitamins A, C and E and the risk of breast cancer: results from a case-control study in Greece. British Journal Of Cancer 1998, 79: 23-29. PMID: 10408688, PMCID: PMC2362172, DOI: 10.1038/sj.bjc.6690006.Peer-Reviewed Original ResearchConceptsΒ-carotene intakeBreast cancer riskCase-control studyBreast cancerOdds ratioCancer riskVitamin ESemiquantitative food frequency questionnaireBreast cancer risk factorsIntake of retinolVitamin CFood frequency questionnaireCancer risk factorsPost-menopausal womenTotal energy intakeΒ-carotene effectPremenopausal womenFrequency questionnaireControl womenVegetable intakeInverse associationRisk factorsDietary compoundsDietary dataSpecific micronutrientsAlcohol and Breast Cancer in Women: A Pooled Analysis of Cohort Studies
Smith-Warner SA, Spiegelman D, Yaun SS, van den Brandt PA, Folsom AR, Goldbohm RA, Graham S, Holmberg L, Howe GR, Marshall JR, Miller AB, Potter JD, Speizer FE, Willett WC, Wolk A, Hunter DJ. Alcohol and Breast Cancer in Women: A Pooled Analysis of Cohort Studies. JAMA 1998, 279: 535-540. PMID: 9480365, DOI: 10.1001/jama.279.7.535.Peer-Reviewed Original ResearchConceptsInvasive breast cancerAlcohol intakeBreast cancerAlcohol consumptionRelative riskIncident invasive breast cancerMultivariate-adjusted relative riskIncident breast cancer casesBeverage-specific alcohol consumptionMultivariate relative riskTotal alcohol intakeFood frequency questionnaireBreast cancer incidenceBreast cancer riskBreast cancer casesRandom-effects modelLong-term intakeCohort studyFrequency questionnaireProspective studyPooled analysisCancer incidenceDiet assessment instrumentsCancer casesNondietary factors
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 modelsChoice