survcondense {survival} R Documentation

## Shorten a (time1, time2) survival dataset

### Description

Counting process data sets can sometimes grow to be unweildy, this can be used to compact one.

### Usage

survcondense(formula, data, subset, weights, na.action= na.pass, id,
start = "tstart", end = "tstop", event = "event")


### Arguments

 formula a formula object, with the response on the left of a ~ operator, and the terms on the right. The response must be a survival object as returned by the Surv function. data a data.frame in which to interpret the variables named in the formula and the id argument argument. subset optional subset expression to apply to the data set weights optional variable name for case weights na.action optional removal of missing values id variable name that identifies subjects start optional character string, giving the name of the start time variable in the result end optional character string, giving the name of the stop time variable in the result event optional character string, giving the name of the event variable in the result

### Details

Through the use of the survSplit and tmerge functions, a counting process data set will gain more and more rows of data. Occassionally it is useful to collapse this surplus back down, e.g., when interest is to be focused on only a few covariates, or for debugging. The right hand side of formula will often have only a few variables, in this use.

If a row of data is censored, and represents the same covariates and identifier as the row below it, then the two rows can be merged together using a single (time1, time2) interval. The compression can sometimes be large.

The start, stop and end options are used when the left hand side of the formula has expressions that are not a simple name, e.g. Surv(time1, time2, death | progression) would be a case where event is used to set the outcome variable's name.

a data frame

### Author(s)

Terry Therneau

survSplit,tmerge

### Examples

dim(aml)
test1 <- survSplit(Surv(time, status) ~ ., data=aml,
cut=c(10, 20, 30), id="newid")
dim(test1)