1996
A simulation study of the number of events per variable in logistic regression analysis
Peduzzi P, Concato J, Kemper E, Holford T, Feinstein A. A simulation study of the number of events per variable in logistic regression analysis. Journal Of Clinical Epidemiology 1996, 49: 1373-1379. PMID: 8970487, DOI: 10.1016/s0895-4356(96)00236-3.Peer-Reviewed Original Research
1995
Importance of events per independent variable in proportional hazards analysis I. Background, goals, and general strategy
Concato J, Peduzzi P, Holford T, Feinstein A. Importance of events per independent variable in proportional hazards analysis I. Background, goals, and general strategy. Journal Of Clinical Epidemiology 1995, 48: 1495-1501. PMID: 8543963, DOI: 10.1016/0895-4356(95)00510-2.Peer-Reviewed Original ResearchImportance of events per independent variable in proportional hazards regression analysis II. Accuracy and precision of regression estimates
Peduzzi P, Concato J, Feinstein A, Holford T. Importance of events per independent variable in proportional hazards regression analysis II. Accuracy and precision of regression estimates. Journal Of Clinical Epidemiology 1995, 48: 1503-1510. PMID: 8543964, DOI: 10.1016/0895-4356(95)00048-8.Peer-Reviewed Original Research
1993
Analysis as‐randomized and the problem of non‐adherence: An example from the veterans affairs randomized trial of coronary artery bypass surgery
Peduzzi P, Wittes J, Detre K, Holford T. Analysis as‐randomized and the problem of non‐adherence: An example from the veterans affairs randomized trial of coronary artery bypass surgery. Statistics In Medicine 1993, 12: 1185-1195. PMID: 8210821, DOI: 10.1002/sim.4780121302.Peer-Reviewed Original ResearchConceptsCoronary artery bypass surgeryArtery bypass surgeryTreatment groupsAlternative treatment groupBypass surgeryTreatment changesVeterans Administration Cooperative StudyTime of randomizationRandomized clinical trialsTreat analysisClinical trialsOutcome eventsRandom treatment assignmentCooperative StudyVeterans AffairsTreatment assignmentTherapySurgeryTrialsGroupPatients
1987
Comparison of the logistic and Cox regression models when outcome is determined in all patients after a fixed period of time
Peduzzi P, Holford T, Detre K, Chan Y. Comparison of the logistic and Cox regression models when outcome is determined in all patients after a fixed period of time. Journal Of Clinical Epidemiology 1987, 40: 761-767. PMID: 3597677, DOI: 10.1016/0021-9681(87)90127-5.Peer-Reviewed Original Research
1982
CLINICAL CHARACTERISTICS AND CIGARETTE SMOKING IN RELATION TO PROGNOSIS OF ANGINA PECTORIS IN FRAMINGHAM
HUBERT H, HOLFORD T, KANNEL W. CLINICAL CHARACTERISTICS AND CIGARETTE SMOKING IN RELATION TO PROGNOSIS OF ANGINA PECTORIS IN FRAMINGHAM. American Journal Of Epidemiology 1982, 115: 231-242. PMID: 7058782, DOI: 10.1093/oxfordjournals.aje.a113295.Peer-Reviewed Original ResearchConceptsAngina pectorisBlood pressureAngina onsetElectrocardiographic findingsUncomplicated angina pectorisCoronary risk factorsFuture coronary eventsElevated blood pressurePowerful independent predictorCigarette smoking habitsLong-term prognosisSystolic blood pressureLong-term followYears of ageLack of associationCoronary eventsCoronary riskBaseline characteristicsSymptom onsetYounger patientsIndependent predictorsPrognostic advantageSmoking habitsAbnormal electrocardiogramCigarette smoking