Surv(time, event) Surv(time, time2, event, type=<<see below>>, origin=0) is.Surv(x)
event
indicates whether an event
occurred at the end of the interval.
time
, 2 = left censored,
and 3 = interval censored.
For left-censored data, the status indicator is T=uncensored, F=censored.
Although unusual, the event indicator can be omitted,
in which case all subjects are assumed to have an event.
"right"
,
"left"
,
"counting"
,
"interval"
,
or
"interval2"
.
The default is
"right"
or
"counting"
depending on whether the
time2
argument is absent or present, respectively.
Surv
, a matrix of 2 or 3
columns of class
"Surv"
containing
time
,
time2
(if provided),
and
status
.
is.Surv
,
a logical value
T
if
x
inherits from class
"Surv"
,
otherwise an
F
.
Surv objects can be subscripted either as an object, e.g.
x[1:3]
using a single subscript;
in which case the
drop
argument is ignored;
or as a matrix, using two arguments.
If the second subscript is missing and
drop=F
,
the result of the subscripting will be a Surv object, e.g.,
x[1:3,,drop=F]
,
otherwise the result will be a matrix (or vector), in accordance with
the default behavior for subscripting matrices.
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 interval is a pair of time points
within which the event is
known to have occurred.
If
type="interval2"
,
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 contains 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.
Surv(leukemia$time, leukemia$status) Surv(heart$start, heart$stop, heart$event)