Split a survival object at specified durations.

Given a survival object, (a matrix with two or three columns) and a set of specified cut times, split each record into multiple subrecords at each cut time. The new survival object will be in `counting process' format, with an enter time, exit time, and event status for each record.

SurvSplit(Y, cuts)

Arguments

Y	A survival object, a matrix with two or three columns.
cuts	The cut points, must be strictly positive and distinct.

Value

A list with components

Y

The new survival object with three columns, i.e., in 'counting process' form.

ivl

Interval No., starting from leftmost, (0, cuts[1]) or similar.

idx

Row number for original Y row.

Note

This function is used in phreg for the piecewise constant hazards model. It uses age.window for each interval.

See also

survSplit, age.window.

Author

Göran Broström

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--  or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function(Y, cuts){
    if (NCOL(Y) == 2) Y <- cbind(rep(0, NROW(Y)), Y)
    indat <- cbind(Y, 1:NROW(Y), rep(-1, NROW(Y)))
    colnames(indat) <- c("enter", "exit", "event", "idx", "ivl")
    n <- length(cuts)
    cuts <- sort(cuts)
    if ((cuts[1] <= 0) || (cuts[n] == Inf))
        stop("'cuts' must be positive and finite.")
    cuts <- c(0, cuts, Inf)
    n <- n + 1
    out <- list()
    indat <- as.data.frame(indat)
    for (i in 1:n){
        out[[i]] <- age.window(indat, cuts[i:(i+1)])
        out[[i]]$ivl <- i
        out[[i]] <- t(out[[i]])
    }
    Y <- matrix(unlist(out), ncol = 5, byrow = TRUE)
    colnames(Y) <- colnames(indat)
    list(Y = Y[, 1:3],
         ivl = Y[, 5],
         idx = Y[, 4]
         )
  }
#> function(Y, cuts){
#>     if (NCOL(Y) == 2) Y <- cbind(rep(0, NROW(Y)), Y)
#>     indat <- cbind(Y, 1:NROW(Y), rep(-1, NROW(Y)))
#>     colnames(indat) <- c("enter", "exit", "event", "idx", "ivl")
#>     n <- length(cuts)
#>     cuts <- sort(cuts)
#>     if ((cuts[1] <= 0) || (cuts[n] == Inf))
#>         stop("'cuts' must be positive and finite.")
#>     cuts <- c(0, cuts, Inf)
#>     n <- n + 1
#>     out <- list()
#>     indat <- as.data.frame(indat)
#>     for (i in 1:n){
#>         out[[i]] <- age.window(indat, cuts[i:(i+1)])
#>         out[[i]]$ivl <- i
#>         out[[i]] <- t(out[[i]])
#>     }
#>     Y <- matrix(unlist(out), ncol = 5, byrow = TRUE)
#>     colnames(Y) <- colnames(indat)
#>     list(Y = Y[, 1:3],
#>          ivl = Y[, 5],
#>          idx = Y[, 4]
#>          )
#>   }
#> <environment: 0x55d7ac694b68>