The methodological advancements made in the field of joint models are numerous. None less, case competing risks has largely been neglected, especially from a practitioner's point view. In relevant works on models, assumptions Gaussian linear longitudinal series and proportional cause-specific hazard functions, amongst others, have remained unchallenged. this article, we provide framework based ...

BACKGROUND Composite end points are frequently used in reports of clinical trials. One rationale for the use of composite end points is to account for competing risks. In the presence of competing risks, the event rate of a specific event depends on the rates of other competing events. One proposed solution is to include all important competing events in one composite end point. Clinical triali...

Competing risks data usually arises in studies in which the failure of an individual may be classified into one of k (k > 1) mutually exclusive causes of failure. When competing risks are present, there are two main differences with classical survival analysis: (i) survival functions are not mainly used to describe cause-specific failures and, (ii) classical estimation techniques may provide bi...

SUMMARY Cause-specific hazard and cumulative incidence function are of practical importance in competing risks studies. Inferential procedures for these quantities are well developed and can be applied to semi-competing risks data, where a terminating event censors a non-terminating event, after coercing the data into the competing risks format. Complications arise when there is left truncation...