rs.diff  R Documentation 
Tests if there is a difference between two or more net survival curves using a logrank type test.
rs.diff( formula = formula(data), data = parent.frame(), ratetable = relsurv::slopop, na.action, precision = 1, rmap )
formula 
A formula expression as for other survival models, of the
form NOTE: The followup time must be in days. 
data 
a data.frame in which to interpret the variables named in the

ratetable 
a table of event rates, organized as a 
na.action 
a missingdata filter function, applied to the model.frame,
after any subset argument has been used. Default is

precision 
Precision for numerical integration. Default is 1, which means that daily intervals are taken, the value may be decreased to get a higher precision or increased to achieve a faster calculation. The calculation intervals always include at least all times of event and censoring as border points. 
rmap 
an optional list to be used if the variables are not organized
and named in the same way as in the 
NOTE: The followup time must be specified in days. The ratetable
being used may have different variable names and formats than the user's
data set, this is dealt with by the rmap
argument. For example, if
age is in years in the data set but in days in the ratetable
object,
age=age*365.241 should be used. The calendar year can be in any date format
(date, Date and POSIXt are allowed), the date formats in the
ratetable
and in the data may differ.
a rsdiff
object; can be printed with print
.
Package: Pohar Perme, M., Pavlic, K. (2018) "Nonparametric Relative Survival Analysis with the R Package relsurv". Journal of Statistical Software. 87(8), 127, doi: "10.18637/jss.v087.i08" Theory: Graffeo, N., Castell, F., Belot, A. and Giorgi, R. (2016) "A logranktype test to compare net survival distributions. Biometrics. doi: 10.1111/biom.12477" Theory: Pavlic, K., Pohar Perme, M. (2017) "On comparison of net survival curves. BMC Med Res Meth. doi: 10.1186/s1287401703513"
rs.surv
, survdiff
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 365.241 in order to be expressed in days. rs.diff(Surv(time,cens)~sex,rmap=list(age=age*365.241), ratetable=slopop,data=rdata)
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