Publication | Closed Access
Estimation of failure probabilities in the presence of competing risks: new representations of old estimators
122
Citations
0
References
1999
Year
PrognosisRare Event EstimationRisk MetricPopulation Health SciencesRisk AnalysisCumulative Incidence EstimateLogistic AnalysisPrognostic AssessmentAdverse EventRisk ManagementClinical EpidemiologyFailure AnalysisBayesian MethodsFailure ProbabilitiesPublic HealthInsuranceStatisticsMedical StatisticGeneral EpidemiologyMedical LiteratureEconomicsDisease Risk AssessmentRiskMarginal Structural ModelsCensored ObservationsFinanceEpidemiologyOld EstimatorsNew RepresentationsTime-varying ConfoundingMedicineFailure Prediction
A topic that has received attention in both the statistical and medical literature is the estimation of the probability of failure for endpoints that are subject to competing risks. Despite this, it is not uncommon to see the complement of the Kaplan–Meier estimate used in this setting and interpreted as the probability of failure. If one desires an estimate that can be interpreted in this way, however, the cumulative incidence estimate is the appropriate tool to use in such situations. We believe the more commonly seen representations of the Kaplan–Meier estimate and the cumulative incidence estimate do not lend themselves to easy explanation and understanding of this interpretation. We present, therefore, a representation of each estimate in a manner not ordinarily seen, each representation utilizing the concept of censored observations being ‘redistributed to the right.’ We feel these allow a more intuitive understanding of each estimate and therefore an appreciation of why the Kaplan–Meier method is inappropriate for estimation purposes in the presence of competing risks, while the cumulative incidence estimate is appropriate. Copyright © 1999 John Wiley & Sons, Ltd.