event.split: EventSplit (SurvSplit).

In timereg: Flexible Regression Models for Survival Data

EventSplit (SurvSplit).

Description

contstructs start stop formulation of event time data after a variable in the data.set. Similar to SurvSplit of the survival package but can also split after random time given in data frame.

Usage

event.split(
  data,
  time = "time",
  status = "status",
  cuts = "cuts",
  name.id = "id",
  name.start = "start",
  cens.code = 0,
  order.id = TRUE,
  time.group = FALSE
)

Arguments

data	data to be split
time	time variable.
status	status variable.
cuts	cuts variable or numeric cut (only one value)
name.id	name of id variable.
name.start	name of start variable in data, start can also be numeric "0"
cens.code	code for the censoring.
order.id	order data after id and start.
time.group	make variable "before"."cut" that keeps track of wether start,stop is before (1) or after cut (0).

Author(s)

Thomas Scheike

Examples

set.seed(1)
d <- data.frame(event=round(5*runif(5),2),start=1:5,time=2*1:5,
		status=rbinom(5,1,0.5),x=1:5)
d

d0 <- event.split(d,cuts="event",name.start=0)
d0

dd <- event.split(d,cuts="event")
dd
ddd <- event.split(dd,cuts=3.5)
ddd
event.split(ddd,cuts=5.5)

### successive cutting for many values 
dd <- d
for  (cuts in seq(2,3,by=0.3)) dd <- event.split(dd,cuts=cuts)
dd

###########################################################################
### same but for situation with multiple events along the time-axis
###########################################################################
d <- data.frame(event1=1:5+runif(5)*0.5,start=1:5,time=2*1:5,
		status=rbinom(5,1,0.5),x=1:5,start0=0)
d$event2 <- d$event1+0.2
d$event2[4:5] <- NA 
d

d0 <- event.split(d,cuts="event1",name.start="start",time="time",status="status")
d0
###
d00 <- event.split(d0,cuts="event2",name.start="start",time="time",status="status")
d00

timereg documentation built on Sept. 11, 2024, 8:35 p.m.