relsurv (version 1.6-5)

rs.surv: Compute a Relative Survival Curve

Description

Computes an estimate of the relative survival curve using the Ederer II method, Pohar-Perme method or the Hakulinen method

Usage

rs.surv(formula, data,ratetable=survexp.us,na.action,fin.date,
	     method="pohar-perme",conf.type="log",conf.int=0.95,type="kaplan-meier")

Arguments

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

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.

na.action

a missing-data filter function, applied to the model.frame, after any subset argument has been used. Default is options()$na.action.

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 relative survival. The options are pohar-perme(default), ederer and hakulinen.

conf.type

one of plain, log (the default), or log-log. The first option causes the standard intervals curve +- k *se(curve), where k is determined from conf.int. The log option calculates intervals based on the cumulative haz

conf.int

the level for a two-sided confidence interval on the survival curve(s). Default is 0.95.

type

defines how survival estimates are to be calculated given the hazards. The default (kaplan-meier) calculates the product integral, whereas the option fleming-harrington exponentiates the negative cumulative hazard. Analogous to

Value

• a survfit object; see the help on survfit.object for details. The survfit methods are used for print, plot, lines, and points.

Details

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. The calculation of the Pohar-Perme estimate is more time consuming since more data are needed from the population tables. The old version of the function, now named rs.survo can be used as a faster version for the Hakulinen and Ederer II estimate.

References

Package. Pohar M., Stare J. (2006) "Relative survival analysis in R." Computer Methods and Programs in Biomedicine, 81: 272--278 Relative survival: Pohar, M., Stare, J. (2007) "Making relative survival analysis relatively easy." Computers in biology and medicine, 37: 1741--1749.

See Also

survfit, survexp

Examples

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)