2025-01-12 00:52:51 +08:00

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R Under development (unstable) (2021-01-28 r79896) -- "Unsuffered Consequences"
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> library(survival)
> aeq <- function(x,y) all.equal(as.vector(x), as.vector(y))
> options(na.action=na.exclude)
> #
> # More tests of factors in prediction, using a new data set
> #
> fit <- coxph(Surv(time, status) ~ factor(ph.ecog), lung)
>
> tdata <- data.frame(ph.ecog = factor(0:3))
> p1 <- predict(fit, newdata=tdata, type='lp')
> p2 <- predict(fit, type='lp')
> aeq(p1, p2[match(0:3, lung$ph.ecog)])
[1] TRUE
>
> fit2 <- coxph(Surv(time, status) ~ factor(ph.ecog) + factor(sex), lung)
> tdata <- expand.grid(ph.ecog = factor(0:3), sex=factor(1:2))
> p1 <- predict(fit2, newdata=tdata, type='risk')
>
> xdata <- expand.grid(ph.ecog=factor(1:3), sex=factor(1:2))
> p2 <- predict(fit2, newdata=xdata, type='risk')
> all.equal(p2, p1[c(2:4, 6:8)], check.attributes=FALSE)
[1] TRUE
>
>
> fit3 <- survreg(Surv(time, status) ~ factor(ph.ecog) + age, lung)
> tdata <- data.frame(ph.ecog=factor(0:3), age=50)
> predict(fit, type='lp', newdata=tdata)
1 2 3 4
0.0000000 0.3688401 0.9163870 2.2079803
> predict(fit3, type='lp', newdata=tdata)
1 2 3 4
6.399571 6.142938 5.770523 4.916993
>
> proc.time()
user system elapsed
0.873 0.036 0.905