Model with hazard per death time...
model {
for (i in 1:N) {
for (j in 1:T) {
Y[i,j] <- step(obs.t[i] - t[j] + eps)
dN[i,j] <- Y[i,j]*step(t[j+1] - obs.t[i] - eps)*ind[i]
}
}
dt[1] <- t[1]
for (j in 2:(T+1)) {
dt[j] <- t[j] - t[j-1]
}
for (j in 1:T) {
for (i in 1:N) {
dN[i,j] ~ dpois(Idt[i,j])
Idt[i,j] <- Y[i,j]*exp(beta*Z[i])
* lam[period[j]]*dt[j]
}
}
cumhaz.treat[1] <- 0
cumhaz.placebo[1] <- 0
for (j in 2:(T+1)) {
cumhaz.treat[j] <- cumhaz.treat[j-1] + lam[period[j]]
* dt[j]*exp(beta*-0.5)
cumhaz.placebo[j] <- cumhaz.placebo[j-1] + lam[period[j]]
* dt[j]*exp(beta*0.5)
S.treat[j] <- exp(-cumhaz.treat[j])
S.placebo[j] <- exp(-cumhaz.placebo[j])
}
for (j in 1:ndtimes) {
lam[j] ~ dgamma(0.001, 0.001)
}
beta ~ dnorm(0.0, 0.000001)
}


Data:
list(N=42, T=23, eps=1.0E-10,
obs.t=c(1,1,2,2,3,4,4,5,5,8,8,8,8,11,11,12,12,15,17,22,23,
6,6,6,6,7,9,10,10,11,13,16,17,19,20,22,23,25,32,32,34,35),
ind=c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,
1,1,1,1,1,0,1,0,1,0,0,1,1,0,0,0,1,1,0,0,0,0,0),
Z=c(0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,
0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,
-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,
-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5),
t=c(1,2,3,4,5,6,7,8,9,10,11,12,13,15,16,17,19,20,22,23,25,32,34,35),
period=c(1,2,3,4,5,6,7,8,8,9,10,11,12,13,14,15,15,15,16,17,17,17,17,17),
ndtimes=17)


Inits:
list(beta = 0.0,
lam = c(0.1,0.1,0.1,0.1,0.1,0.1,0.1,0.1,0.1,
0.1,0.1,0.1,0.1,0.1,0.1,0.1,0.1))


Click arrow for statistics and DIC

Model with four distinct hazard pieces...
model{
for (i in 1:N) {
for (j in 1:T) {
Y[i,j] <- step(obs.t[i] - t[j] + eps)
dN[i,j] <- Y[i,j]*step(t[j+1] - obs.t[i] - eps)*ind[i]
}
}
dt[1] <- t[1]
for (j in 2:(T+1)) {
dt[j] <- t[j] - t[j-1]
}
for (j in 1:T) {
for (i in 1:N) {
dN[i,j] ~ dpois(Idt[i,j])
Idt[i,j] <- Y[i,j] * exp(beta*Z[i]) * lam[period4[j]]*dt[j]
}
}
cumhaz.treat[1] <- 0
cumhaz.placebo[1] <- 0
for (j in 2:(T+1)) {
cumhaz.treat[j] <- cumhaz.treat[j-1] + lam[period4[j]]
* dt[j]*exp(beta*-0.5)
cumhaz.placebo[j] <- cumhaz.placebo[j-1] + lam[period4[j]]
* dt[j]*exp(beta*0.5)
S.treat[j] <- exp(-cumhaz.treat[j])
S.placebo[j] <- exp(-cumhaz.placebo[j])
}
for (j in 1:4) {
lam[j] ~ dgamma(0.001, 0.001)
}
beta ~ dnorm(0.0, 0.000001)
}

Data:
list(N=42, T=23, eps=1.0E-10,
obs.t=c(1,1,2,2,3,4,4,5,5,8,8,8,8,11,11,12,12,15,17,22,23,
6,6,6,6,7,9,10,10,11,13,16,17,19,20,22,23,25,32,32,34,35),
ind=c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,
1,1,1,1,1,0,1,0,1,0,0,1,1,0,0,0,1,1,0,0,0,0,0),
Z=c(0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,
0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,
-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,
-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5,-0.5),
t=c(1,2,3,4,5,6,7,8,9,10,11,12,13,15,16,17,19,20,22,23,25,32,34,35),
period4=c(1,1,1,1,1,1,2,2,2,2,2,2,3,3,3,3,3,3,4,4,4,4,4,4))

Inits:
list(beta = 0.0, lam = c(0.1, 0.1, 0.1, 0.1))

Click arrow for statistics and DIC