data {
      cadj <- 100000
      for(i in 1 : N ) {
      zeros[i] <- 0
      }
      }

model{	

   for(i in 1 : N) {
      
      ###joint model###

      #### hazard
      mu[i]<-exp(alpha[ext[i]]+beta2*trt[i])  #control arm: trt[i]==0, treatment arm: trt[i]==1, HC: ext=2, Trial: ext=1

      l[i] <- r0*mu[i]*pow(timev[i],r0-1)
      
      #### cumulative hazard
      HL[i] <- mu[i] * pow(timev[i],r0)
      
      L[i] <-    pow(l[i], event[i])  * exp(-HL[i]) #censor: event[i]==0
      
      phi[i] <-  -log (L[i]) + cadj

      zeros[i] ~ dpois( phi[i] )     # likelihood is exp(-phi[i])
      }
      
      ### prior 
      alpha[1] ~ dnorm(alpha[2],tau)
      alpha[2] ~ dnorm(0, 0.001) #historical parameter
      
      beta2 ~ dnorm(0, 1)
      
      sigma ~ dt(0, 25, 1)
	
	    tau<- 1/(sigma^2)
      
      r0 ~ dexp(1)
      
      HR_trt_cc=exp(beta2)
      HR_cc_hc=exp(alpha[1]-alpha[2])
      cc_hc=alpha[1]-alpha[2]
      
      }