check.survMCOD: Produce plots to check convergence of multiple-cause model
In moreno-betancur/survMCOD: Survival analysis with multiple causes of death

Description Usage Arguments Details References Examples

Produce plots to check convergence of multiple-cause model

1	check.survMCOD(fit)

fit

A model fit returned by survMCOD.

The plots produced show Iter+2 estimates of each parameter, where Iter is the number of iterations specified by the user in the call to survMCOD. The first two estimates correspond to a starting value and an improved starting value (see Moreno-Betancur et al. 2017 for details). Healthy convergence is seen by curves showing variation in estimates across the first three points, followed by a stabilisation of the curve around the final estimate.

Moreno-Betancur M, Sadaoui H, Piffaretti C, Rey G. Survival analysis with multiple causes of death: Extending the competing risks model. Epidemiology 2017; 28(1): 12-19.

  ## Example ## uncomment to run

  # First we simulate data using the simMCOD function:
  # datEx<-simMCOD(n=1000,xi=-1,rho=-2,phi=0,
  #       pgen=c(1,0,0.75,0.25,0.125,0.083),
  #      lambda=0.001,v=2,pUC=c(1,0.75))

  # Run analysis

  # fitMCOD<-survMCOD(SurvM(time=TimeEntry,time2=TimeExit,status=Status,
  #                       weight=Pi)~X1,
  #                  formOther=~Z1,data=datEx,UC_indicator="UC")

  # Check convergence of multiple-cause analysis
  # check.survMCOD(fitMCOD)