Public HealthBiostatisticsEpidemiologyProbability TheoryStochastic ProcessesCompeting RisksDependence ModelingDisease CausationInferential StatisticsProbability DistributionsStatistical InferenceConditional Independence AssumptionCopula ModelsCopula-based Dependence ModelingDependence StructureIndependenceMultiple Decrement TheoryMultiple-decrement ModelsParameter Identifiability
Currently, multiple decrement theory is based on the assumption that competing causes of decrement are stochastically independent, even though this assumption is usually not true in reality. This paper presents well-known results in the theory of dependent competing risks that are fun-damental in extending multiple decrement theory towards a dependent decrement theory. First, the state of the art is examined and the results that are based on the independence assumption are identified. Next, we use the well-developed theory of copula functions to model dependence, and we present a theorem that characterizes the mathematical relationship between the crude and net probabilities when the decrements are depen-dent. We also discuss the issue of identifiability and the related issue of measuring the effect of removing causes of decrement. Finally, we use an identifiability result to analyze the effect of removing heart/cerebro-vascular diseases from the U.S. population when these diseases are cor-related to other: causes of death. I.
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Ordinal Measures of Association
William Kruskal · Journal of the American Statistical Association · 1958 · 528 citations
The identifiability of the competing risks model
James J. Heckman, Bo E. Honoré · Biometrika · 1989 · 303 citations