A Cox-log-linear model for competing risk data
by Dr Meei Ng
Abstract: Competing risk data arise frequently in medical studies where failures can be classified into various types. The current methods of analyzing such data are based on modeling each cause-specific hazard function on its own using standard survival analysis techniques, or non-parametric pairwise comparison of the cumulative incidence functions of treatment groups. These methods have disadvantages that are well known, and will be discussed. We propose a new method of modelling that provides a single baseline hazard function, and allows parametric overall (and pairwise) comparison of cause-specific hazard functions and cumulative incidence functions. It also enables the incorporation of covariate information. An example will be used to illustrate the procedures.
For More Information: Dr Owen Jones: firstname.lastname@example.org