relsurv (version 2.2-3)

nessie: Net Expected Sample Size Is Estimated

Description

Calculates how the sample size decreases in time due to population mortality

Usage

nessie(formula, data, ratetable = relsurv::slopop,times,rmap)

Arguments

formula

a formula object, same as in rs.surv. The right-hand side of the formula object includes the variable that defines the subgroups (a variable of type factor) by which the expected sample size is to be calculated.

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 slopop.

times

Times at which the calculation should be evaluated - in years!

rmap

an optional list to be used if the variables are not organized and named in the same way as in the ratetable object. See details of the rs.surv function.

Value

A list of values.

Details

The function calculates the sample size we can expect at a certain time point if the patients die only due to population causes (population survival * initial sample size in a certain category), i.e. the number of individuals that remains at risk at given timepoints after the individuals who die due to population causes are removed. The result should be used as a guideline for the sensible length of follow-up interval when calculating the net survival.

The first column of the output reports the number of individuals at time 0. The last column of the output reports the conditional expected (population) survival time for each subgroup.

References

Pohar Perme, M., Pavlic, K. (2018) "Nonparametric Relative Survival Analysis with the R Package relsurv". Journal of Statistical Software. 87(8), 1-27, doi: "10.18637/jss.v087.i08"

See Also

rs.surv

Examples

# NOT RUN {
data(slopop)
data(rdata)
rdata$agegr <-cut(rdata$age,seq(40,95,by=5))
nessie(Surv(time,cens)~agegr,rmap=list(age=age*365.241),
	ratetable=slopop,data=rdata,times=c(1,3,5,10,15))
# }