survexp.fit {survival}  R Documentation 
Compute expected survival. This function is not to be called by the user.
survexp.fit(x, y, times, death, ratetable)
x 
a matrix. The first column contains the group,
an integer value that divides the subjects into subsets.
Remaining columns must match the dimensions of the ratetable ,
in the correct order.

y 
the follow up time for each subject. 
times 
the vector of times at which a result will be computed. 
death 
death indicator 
ratetable 
a rate table, such as survexp.uswhite .

For cohort survival it must be the potential censoring time for each subject, ignoring death.
For an exact estimate times
should be a superset of y
, so that each
subject at risk is at risk for the entire subinterval of time.
For a large data set, however, this can use an inordinate amount of
storage and/or compute time. If the times
spacing is more coarse than
this, an actuarial approximation is used which should, however, be extremely
accurate as long as all of the returned values are > .99.
For a subgroup of size 1 and times
> y
,
the conditional method reduces to exp(h) where
h is the expected cumulative hazard for the subject over his/her
observation time. This is used to compute individual expected survival.
A list containing the number of subjects and the expected survival(s) at each time point. If there are multiple groups, these will be matrices with one column per group.
Most users will call the higher level routine survexp
.
Consequently, this function has very few error checks on its input arguments.