60 lines
2.2 KiB
R
60 lines
2.2 KiB
R
library(survival)
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# Make sure that the old-style and new-style calls both work
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# new style
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vet2 <- survSplit(Surv(time, status) ~ ., data= veteran, cut=c(90, 180),
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episode= "tgroup", id="id")
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vet2[1:7, c("id", "tstart", "time", "status", "tgroup", "age", "karno")]
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# old style
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vet3 <- survSplit(veteran, end='time', event='status', cut=c(90,180),
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episode="tgroup", id="id")
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all.equal(vet2, vet3)
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all.equal(nrow(vet2), nrow(veteran) + sum(veteran$time >90) +
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sum(veteran$time > 180))
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# Do a parallel computation using survSplit, and pyears/tcut. We should get
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# the same answer.
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# Break subjects up by year of entry and current time on study. Most of
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# the deaths are within 3 months
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# pyears complains (justifiably) about the obs with 0 days of fu, so we add 1
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#
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data1 <- jasa
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data1$ayear <- as.numeric(substring(as.character(jasa$accept.dt), 1,4))
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temp <- round(c(0, .25, 1,2,5)*365.25) # years
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ftime <- tcut(rep(0, nrow(jasa)), temp,
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labels=paste(c(0, .25, 1:2), c(.25, 1,2,5), sep='-'))
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pfit <- pyears(Surv(futime +1,fustat) ~ ayear + ftime, data1,
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scale=1)
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data2 <- survSplit(Surv(futime+1, fustat) ~ ., cut=temp, data=data1,
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episode = "tgroup")
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tab1 <- with(data2, tapply(fustat, list(ayear, tgroup), sum))
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tab1 <- ifelse(is.na(tab1), 0, tab1)
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all.equal(as.vector(tab1), as.vector(pfit$event)) # ignore dimnames
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tab2 <- with(data2, tapply(tstop-tstart, list(ayear, tgroup), sum))
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tab2 <- ifelse(is.na(tab2), 0, tab2)
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all.equal(as.vector(tab2), as.vector(pfit$pyears))
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# double check that the "data" option gives the same values
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pfit2 <- pyears(Surv(futime +1,fustat) ~ ayear + ftime, data1,
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scale=1, data.frame=TRUE)$data
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all.equal(pfit2$pyears, pfit$pyears[pfit$pyears >0])
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all.equal(pfit2$event, pfit$event[pfit$pyears >0])
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# and that the rows of data2 have the right labels
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keep <- which(pfit$pyears >0) # these are not in the data
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rname <- rownames(pfit$pyears)[row(pfit$pyears)[keep]]
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all.equal(rname, as.character(pfit2$ayear))
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cname <- colnames(pfit$pyears)[col(pfit$pyears)[keep]]
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all.equal(cname, as.character(pfit2$ftime))
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