The competing risks methodology that has been developed in the
statistical literature is ideally suited for modelling a decision-making
process where we have a set of underlying but possibly different
socio-demographic forces pulling a student towards one or other
particular outcome. Given a medical setting, for example, one may be
concerned with identifying potential factors that affect the length of
time that it takes for someone to die from one of a mutually exclusive
set of possible causes; for example, death from a stroke, death from
cancer or death from a liver-related disease. The occurrence of one
type of death will obviously prevent any one of the other events from
occurring. Environmental and genetic factors may, however, be pushing
the individual towards one or more possible causes of death. By
incorporating this information into one’s analysis, one is separating a
competing risks problem from that of a more typical survival analysis
based problem in which the focus rests solely on a primary cause of
death with the other potential causes of death (and their effect on the
primary cause) not being explicitly modelled (as potential competitors
for the final outcome on an individual) in the model-building process.