rs.surv {relsurv} | R Documentation |
Computes an estimate of the relative survival curve using the Kaplan-Meier method for the observed and the Hakulinen method for the expected survival.
rs.surv(formula, data,ratetable=survexp.us,fin.date,method="hakulinen",...)
formula |
a formula object, with the response as a Surv object on the
left of a ~ operator, and, if desired, terms separated by
the + operator on the right. If the variables are not
organized and named in the same way as in the population
tables, a ratetable term must be added to match each
subject to his/her expected cohort. For a single survival curve the ~ 1 part of the
formula is not required.
NOTE: The time must be in days, and the same is required for the ratetable variables (the variables used in the population tables), for example age and year (year must be given in the date format, i.e. in number of days since 01.01.1960).
|
data |
a data.frame in which to interpret the variables named in the
formula .
|
ratetable |
a table of event rates, organized as a ratetable object,
such as survexp.us .
|
fin.date |
The date of the study ending, used for calculating the
potential follow-up times in the Hakulinen method. If
missing, it is calculated as max(year+time) .
|
method |
The method for calculating the expected survival. The options are hakulinen (default) and conditional , see survexp for details. |
... |
other arguments will be passed to the survfit function that
calculates the observed survival.
|
NOTE: All times used in the formula argument must be specified in days. This is true for the follow-up time as well as for
any variables needed ratetable
object, like age
and year
. On the contrary, the int
argument requires
interval specification in years.
The potential censoring times needed for the calculation of the expected survival by the Hakulinen method
are calculated automatically. The times of censoring are left as they are, the times of events are replaced with
fin.date - year
.
a survfit
object; see the help on survfit.object
for details.
The survfit
methods are used for print
,
plot
, lines
, and points
.
survfit
,
survexp
data(slopop) data(rdata) #calculate the relative survival curve #note that the variable year is given in days since 01.01.1960 and that #age must be multiplied by 365 in order to be expressed in days. rs.surv(Surv(time,cens)~sex+ratetable(age=age*365,sex=sex, year=year),ratetable=slopop,data=rdata)