Biometrical Journal · 1995 · 38 citations · 16 references
Public HealthBiostatisticsCancer EpidemiologyEpidemiologic MethodsEpidemiologyCancer MortalityCompeting RisksDependence ModelingDisease CausationMortality ModelingSurvival ModelingCancer Mortality ModelingCause-specific Survival ProbabilitiesCopula EstimationCopula ModelsCopula-based Risk ModelingIdentifiability ProblemNonlinear Differential-algebraic EquationsNonlinear Identifiability
Abstract This paper presents an identifiability theorem in the theory of dependent competing risks and it applies the result by examining the effect of removing cancer from the United States population when cancer is correlated with the other causes of death. The paper shows how dependence can be modeled with copula functions and it shows that calculating the survival probabilities after cancer is removed is equivalent to solving a system of nonlinear differential equations.
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Survival Models and Data Analysis
André I. Khuri · Journal of Quality Technology · 1981 · 609 citations
Ordinal Measures of Association
William Kruskal · Journal of the American Statistical Association · 1958 · 528 citations