fit0	<- coxph(Surv(futime, status) ∼ x1 + x2 + x3, data=data0)
p	<- log(predict(fit0, newdata=data1, type=“expected”))
lp	<- predict(fit0, newdata=data1, type=“lp”)
logbase	<- p − lp
fit1	<- glm(y ∼ offset(p), family=poisson, data=data1)
fit2	<- glm(y ∼ lp + offset(logbase), family=poisson, data=data1)
group	<- cut(lp, c(-Inf, quantile(p,(1:9)/10, Inf))
fit3	<- glm(y ∼ −1+ group + offset(p), family=poisson, data=data1)