
AbstractThis note considers association between nonnegative random variables in which the two observed survival times depend on an unobservable random variable via the proportional hazard model. When the random variables are subject to censoring, the conditional hazard functions provides a reasonable means of describing the association between the two variables. A numerical example demonstrating association in disease incidence in ordered pairs of individuals is analysed. Also, examples of distributions satisfying the notions of dependence considered are provided.
Measures of association (correlation, canonical correlation, etc.), survival times, proportional hazards model, nonnegative random variables, positive dependence, association, survival function, Applications of statistics to biology and medical sciences; meta analysis, censoring, disease incidence, partial differential equations, epidemiology, conditional hazard functions
Measures of association (correlation, canonical correlation, etc.), survival times, proportional hazards model, nonnegative random variables, positive dependence, association, survival function, Applications of statistics to biology and medical sciences; meta analysis, censoring, disease incidence, partial differential equations, epidemiology, conditional hazard functions
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