R Under development (unstable) (2019-06-28 r76752) -- "Unsuffered Consequences"
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> library(survival)
> # Make sure that the old-style and new-style calls both work
> 
> # new style
> vet2 <- survSplit(Surv(time, status) ~ ., data= veteran, cut=c(90, 180), 
+                   episode= "tgroup", id="id")
> vet2[1:7, c("id", "tstart", "time", "status", "tgroup", "age", "karno")]
  id tstart time status tgroup age karno
1  1      0   72      1      1  69    60
2  2      0   90      0      1  64    70
3  2     90  180      0      2  64    70
4  2    180  411      1      3  64    70
5  3      0   90      0      1  38    60
6  3     90  180      0      2  38    60
7  3    180  228      1      3  38    60
> 
> # old style
> vet3 <- survSplit(veteran, end='time', event='status', cut=c(90,180),
+                   episode="tgroup", id="id")
> all.equal(vet2, vet3)
[1] TRUE
> 
> all.equal(nrow(vet2), nrow(veteran) + sum(veteran$time >90) + 
+                       sum(veteran$time > 180))
[1] TRUE
> 
> 
> # Do a parallel computation using survSplit, and pyears/tcut.  We should get
> #  the same answer.
> # Break subjects up by year of entry and current time on study.  Most of
> #  the deaths are within 3 months
> # pyears complains (justifiably) about the obs with 0 days of fu, so we add 1
> #
> data1 <- jasa
> data1$ayear <- as.numeric(substring(as.character(jasa$accept.dt), 1,4))
> temp <- round(c(0, .25, 1,2,5)*365.25)   # years
> ftime <- tcut(rep(0, nrow(jasa)), temp, 
+                   labels=paste(c(0, .25, 1:2), c(.25, 1,2,5), sep='-'))
> pfit <- pyears(Surv(futime +1,fustat) ~ ayear + ftime, data1,
+                scale=1)
> 
> data2 <- survSplit(Surv(futime+1, fustat) ~ ., cut=temp, data=data1,
+                    episode = "tgroup")
> 
> tab1 <- with(data2, tapply(fustat, list(ayear, tgroup), sum))
> tab1 <- ifelse(is.na(tab1), 0, tab1)
> 
> all.equal(as.vector(tab1), as.vector(pfit$event))  # ignore dimnames
[1] TRUE
> 
> tab2 <- with(data2, tapply(tstop-tstart, list(ayear, tgroup), sum))
> tab2 <- ifelse(is.na(tab2), 0, tab2)
> 
> all.equal(as.vector(tab2), as.vector(pfit$pyears))
[1] TRUE
> 
> # double check that the "data" option gives the same values
> pfit2 <- pyears(Surv(futime +1,fustat) ~ ayear + ftime, data1,
+                scale=1, data.frame=TRUE)$data
> all.equal(pfit2$pyears, pfit$pyears[pfit$pyears >0])
[1] TRUE
> all.equal(pfit2$event,  pfit$event[pfit$pyears >0])
[1] TRUE
> 
> # and that the rows of data2 have the right labels
> keep <- which(pfit$pyears >0)  # these are not in the data
> rname <- rownames(pfit$pyears)[row(pfit$pyears)[keep]]
> all.equal(rname, as.character(pfit2$ayear))
[1] TRUE
> 
> cname <- colnames(pfit$pyears)[col(pfit$pyears)[keep]]
> all.equal(cname, as.character(pfit2$ftime))
[1] TRUE
> 
>                    
> 
> proc.time()
   user  system elapsed 
  0.764   0.032   0.805