46 lines
1.7 KiB
R
46 lines
1.7 KiB
R
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library(survival)
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# Strata by covariate interactions, a case pointed out in early 2011
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# by Frank Harrell, which as it turns out had never been computed
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# correctly by any version of the package. Which shows how often this
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# case arises in practice.
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#
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aeq <- function(x, y, ...) all.equal(as.vector(x), as.vector(y))
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fit1 <- coxph(Surv(time, status) ~ wt.loss + age*strata(sex) + strata(ph.ecog),
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data=lung)
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tdata <- data.frame(wt.loss=c(10,5,0,10, 15,20,25),
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age =c(50,60,50,60,70,40,21),
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sex =c(1,1,2,2,1,1,1),
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ph.ecog=c(0,0,1,1,2,2,2))
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surv1 <- survfit(fit1, newdata=tdata)
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fit2 <- coxph(Surv(time, status) ~ wt.loss + age + I(age*0), data=lung,
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init=fit1$coefficients, iter=0, subset=(sex==1 & ph.ecog==0))
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fit2$var <- fit1$var
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surv2 <- survfit(fit2, newdata=list(wt.loss=c(10,5), age=c(50,60)))
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s1 <- surv1[1:2]
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aeq(s1$surv, surv2$surv) #first a vector, second a matrix
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aeq(s1$std.err, surv2$std.err)
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aeq(s1[1]$time, surv2$time)
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aeq(s1[1]$n.event, surv2$n.event)
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fit3 <- coxph(Surv(time, status) ~ wt.loss + age + I(age*1),
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data=lung, init=fit1$coefficients, iter=0,
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subset=(sex==2 & ph.ecog==1))
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fit3$var <- fit1$var
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surv3 <- survfit(fit3, newdata=list(wt.loss=c(0,10), age=c(50,60)))
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aeq(surv1[3:4]$surv, surv3$surv)
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aeq(surv1[3:4]$std, surv3$std)
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fit4 <- coxph(Surv(time, status) ~ wt.loss + age + I(age*0),
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data=lung, init=fit1$coefficients, iter=0,
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subset=(sex==1 & ph.ecog==2))
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fit4$var <- fit1$var
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surv4 <- survfit(fit4, newdata=list(wt.loss=c(15,20,25), age=c(70,40,21)))
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aeq(surv1[5:7]$surv, surv4$surv)
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aeq(surv1[5:7]$std.err, surv4$std.err)
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aeq(surv1[5]$n.risk, surv4$n.risk)
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