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A note on including time-dependent covariate in regression model for competing risks data.

A Latouche·R Porcher·S Chevret
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Abstract

Recently, regression analysis of the cumulative incidence function has gained interest in competing risks data analysis, through the model proposed by Fine and Gray (JASA 1999; 94: 496-509). In this note, we point out that inclusion of time-dependent covariates in this model can lead to serious bias. We illustrate the problems arising in such a context, using bone marrow transplant data as a working example and numerical simulations. Practical advices are given, preventing the misuse of this model.

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AlgorithmsAnalysis of VarianceBiasBone Marrow TransplantationChildGraft vs Host DiseaseHumansLeukemiaLongitudinal StudiesModels, StatisticalMonte Carlo MethodProbabilityProportional Hazards ModelsRecurrenceRegression AnalysisRisk AssessmentSurvival AnalysisSurvival RateJournal Article

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A Latouche, R Porcher, S Chevret. 2005. A note on including time-dependent covariate in regression model for competing risks data.. https://doi.org/10.1002/bimj.200410152

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