jm.DIC: Computes DIC for Bayesian fit of the joint model

In sa4khan/AFTjmr: Recurrent event analysis and joint modeling using accelerated failure time (AFT) models

Description

Returns DIC.

Usage

jm.DIC(bayes.fit, posterior.mean = TRUE)

Arguments

bayes.fit	a fit of the joint model using jmreg.aft.
posterior.mean	if TRUE posterior means are used to compute Dbar and Dhat; if FALSE, posterior medians are used to compute Dbar and Dhat.

Details

See the WinBUGS website for definition of DIC (https://www.mrc-bsu.cam.ac.uk/software/bugs/the-bugs-project-dic/).

Value

Returns pD and DIC.

Author(s)

Shahedul Khan <[e-mail]>

See Also

jmreg.aft,jm.summary, jm.WAIC

Examples

  data(pbc.long)
  data(pbc.surv)
  agec<-pbc.surv$age-mean(pbc.surv$age)
  pbc.surv0<-data.frame(pbc.surv,agec=agec)
# use natural splines
  lme.fit<-lme(log(bilirubin)~drug+ns(futime,2),data=pbc.long,
         random=~ns(futime,2)|id)
  surv.fit<-coxph(Surv(st,status2)~drug*agec,data=pbc.surv0,x=TRUE)
# use rand.model="ns"
  jmfit.w<-jmreg.aft(surv.fit=surv.fit,lme.fit=lme.fit,
          surv.model="weibull",rand.model="ns",timevar="futime",
          n.chain=2,n.adapt = 5000, n.burn = 15000, 
          n.iter = 150000, n.thin = 5)
  jm.DIC(jmfit.w)

sa4khan/AFTjmr documentation built on March 12, 2020, 1:24 a.m.