The package "relsurv" can calculate relative survival. Input are your data (in my case patients diagnosed with colorectal cancer) and then the rate table which includes the change of surviving to the next age category, generally split by sex and year of diagnosis.
In my case, I want to have relative survival according to age, sex, year of diagnosis and socio-economic score. I have all the data that should go into the rate table in 1 data frame:
> head(lifetable)
sex seifa age 2007 2008 2009 2010 2011 2012 2013
1 female SEIFA1 0 0.9947100 0.9953400 0.9956200 0.9959200 0.9964100 0.9966000 0.9966800
2 female SEIFA1 1 0.9996625 0.9996613 0.9997038 0.9996489 0.9996425 0.9996667 0.9997556
3 female SEIFA1 2 0.9997750 0.9997968 0.9998105 0.9998119 0.9998350 0.9998167 0.9998656
4 female SEIFA1 3 0.9998375 0.9998374 0.9998460 0.9998621 0.9998625 0.9998667 0.9999022
5 female SEIFA1 4 0.9998750 0.9998645 0.9998697 0.9998871 0.9998900 0.9999000 0.9999267
6 female SEIFA1 5 0.9998827 0.9999077 0.9998887 0.9998956 0.9999037 0.9999160 0.9999280
I am looking for a quick and easy way to transform this into the 'ratetable'. I searched a lot but found nothing... Anyone?