SurvS4(time, time2, event, type =, origin = 0)
is.SurvS4(x)TRUE/FALSE (TRUE = death) or 1/2 (2=death). For
interval censored data, the status indicator is 0=right censored,
1=event at time(start, end]. For counting process
data, event indicates whethe"right", "left", "counting",
"interval", or "interval2". The default is
"right" or "couSurvS4 (formerly Surv).
There are methods for print, is.na, and
subscripting survival objects. SurvS4 objects are
implemented as a matrix of 2 or 3 columns. In the case of is.SurvS4, a logical value
TRUE if x inherits from class
"SurvS4", otherwise a FALSE.
In theory it is possible to represent interval censored data without a third column containing the explicit status. Exact, right censored, left censored and interval censored observation would be represented as intervals of (a,a), (a, infinity), (-infinity,b), and (a,b) respectively; each specifying the interval within which the event is known to have occurred.
If type = "interval2" then the representation given
above is assumed, with NA taking the place of infinity.
If `type="interval" event must be given.
If event is 0, 1, or 2,
the relevant information is assumed to be contained in
time, the value in time2 is ignored, and the
second column of the result will contain a placeholder.
Presently, the only methods allowing interval
censored data are the parametric models computed by
survreg, so the distinction between
open and closed intervals is unimportant. The distinction
is important for counting process data and the Cox model.
The function tries to distinguish between the use of 0/1
and 1/2 coding for left and right censored data using
if (max(status)==2). If 1/2 coding is used and all
the subjects are censored, it will guess wrong. Use 0/1
coding in this case.
SurvS4-class,
cenpoisson,
survreg,
leukemia.with(leukemia, SurvS4(time, status))
class(with(leukemia, SurvS4(time, status)))Run the code above in your browser using DataLab