I'm trying to use the 'relsurv' package in R to compare the survival of a cohort to national life tables. The code below shows my problem using the example from relsurv but changing the life-table data. I've just used two years and two ages in the life-table data below, the actual data is much larger but gives the same error. The error is 'invalid ratetable argument' but I've formatted it as per the example life-tables 'slopop' and 'survexp.us'.
library(survival)
library(relsurv)
data(rdata) # example data from relsurv
raw = read.table(header=T, stringsAsFactors = F, sep=' ', text='
Year Age sex qx
1980 30 1 0.00189
1980 31 1 0.00188
1981 30 1 0.00191
1981 31 1 0.00191
1980 30 2 0.00077
1980 31 2 0.00078
1981 30 2 0.00076
1981 31 2 0.00074
')
ages = c(30,40) # in years
years = c(1980, 1990)
rtab = array(data=NA, dim=c(length(ages), 2, length(years))) # set up blank array: ages, sexes, years
for (y in unique(raw$Year)){
for (s in 1:2){
rtab[ , s, y-min(years)+1] = -1 * log(1-subset(raw, Year==y&sex==s)$qx) / 365.24 # probability of death in next year, transformed to hazard (see ratetables help)
}
}
attributes(rtab)$dimnames[[1]] = as.character(ages)
attributes(rtab)$dimnames[[2]] = c('male','female')
attributes(rtab)$dimnames[[3]] = as.character(years)
attributes(rtab)$dimid <- c("age", "sex", 'year')
attributes(rtab)$dim <- c(length(ages), 2, length(years))
attributes(rtab)$factor = c(0,0,1)
attributes(rtab)$type = c(2,1,4)
attributes(rtab)$cutpoints[[1]] = ages*365.24 # must be in days
attributes(rtab)$cutpoints[[2]] = NULL
attributes(rtab)$cutpoints[[3]] = as.date(paste("1Jan", years, sep='')) # must be date
attributes(rtab)$class = "ratetable"
# example from relsurv
rsmul(Surv(time,cens) ~ sex+as.factor(agegr)+
ratetable(age=age*365.24, sex=sex, year=year),
data=rdata, ratetable=rtab, int=1)
Try using the transrate function from the relsurv package to reformat the data. That should give you a compatible dataset.
Regards, Josh