摘要：Joint modelling of longitudinal and survival data has received much attention in the
recent years and is becoming increasingly used in clinical studies. When the longitudinal
outcome and survival endpoints are associated, the many well-established
models with different specifications proposed to analyse separately longitudinal and
time-to-event outcomes are not suitable to analyse such data and a joint modelling
approach is required. Although some joint models were adapted in order to allow
for competing endpoints, this methodology has not been widely disseminated. The
present study has as main objective to model jointly longitudinal and survival data
in a competing risk context, discussing the different parameterisations of systematic
implementations of these models in the R, using a real data set as an example for
the comparison between the different model approaches. The relevance of this issue
is associated with the need to draw attention of the users of this statistical software
to the different interpretations of model parameters when fitting these models. To
reinforce the relevance of these models in clinical research, we give an example of a
data set on peritoneal dialysis that was analysed in this context, where death/transfer
to haemodialysis was the event of interest and renal transplant was the competing
event. Joint modelling results were also compared to separate analysis for these data.
