# load data
data(stan)

# fit the model and evaluate
stan.fit <- gssanova(cbind(time+.01,status)~age,
                     data=stan,family="weibull",ext=1/(64-12))
uu <- seq(11,65,length=201)
est <- predict(stan.fit,data.frame(age=uu),se=TRUE,include="age")

# plot the fit
const <- predict(stan.fit,stan,inc="1")[1]
plot(stan$age,stan$time/exp(const),type="n",
     xlab="age at transplant",
     ylab=expression(e^{mu[u](u)}==e^{-eta[u]/alpha}))
points(stan$age,stan$time/exp(const),
       pch=c("+","o")[stan$status+1],col=c(6,3)[stan$status+1])
lines(uu,exp(est$fit),col=4)
lines(uu,exp(est$fit+1.96*est$se),col=5)
lines(uu,exp(est$fit-1.96*est$se),col=5)