Bias by censoring for competing events in survival analysis
Maarten Coemans, Geert Verbeke, Bernd Döhler, Caner Süsal, Maarten Naesens
Abstract
Censoring competing events is common in medical studies and this throughout all specialties By censoring competing events, traditional survival techniques such as the Kaplan-Meier method and the Cox model provide upward biased estimators of the cumulative incidence of an event of interest This bias increases with time and with higher incidences of the competing event To obtain an unbiased estimator of the cumulative incidence of an event of interest, competing event censoring should be abandoned, in favour of competing risks methods on 12 August
Topics & Concepts
Censoring (clinical trials)Survival analysisEstimatorEconometricsCumulative incidenceStatisticsParametric statisticsProportional hazards modelCohortParametric modelDemographyMathematicsSociologyLiver Disease Diagnosis and TreatmentStatistical Methods and InferenceAdvanced Causal Inference Techniques