hey @kostas.danis
not used {epitools} in a while but it is a bit unweildly - it doesnt like dataframes and the 2x2 needs to be in a specific format (explained in the details section of the helpfile).
You need to provide the counts as a matrix - and give the case and control numbers, it calculates totals by itself.

The alternative option as in example 2 below (and described in this post) is to recreate a linelist from the aggregated data. Then using that linelist you could use {gtsummary} to get risk ratios as described here

Example 1: {epitools}

library(epitools)
## as a data frame just to look at (and ensure matrix below is correct)
data <- data.frame(
group = c("Exposed", "Unexposed"),
cases = c(4602, 13), # Number of cases
control = c(136079, 534) # number of controls
)
## create 2x2 table as a matrix
dat <- matrix(
c(4602, 136079, 13, 534), ## input numbers of cases and controls
2,2, ## define dimensions of table
byrow=TRUE) ## input numbers above row-wise
## produce risk ratio
riskratio(dat, ## input matrix
rev = "both") ## flip rows and columns to input correctly
#> $data
#> Outcome
#> Predictor Disease2 Disease1 Total
#> Exposed2 534 13 547
#> Exposed1 136079 4602 140681
#> Total 136613 4615 141228
#>
#> $measure
#> risk ratio with 95% C.I.
#> Predictor estimate lower upper
#> Exposed2 1.000000 NA NA
#> Exposed1 1.376433 0.8038413 2.356894
#>
#> $p.value
#> two-sided
#> Predictor midp.exact fisher.exact chi.square
#> Exposed2 NA NA NA
#> Exposed1 0.2365873 0.2781665 0.2401614
#>
#> $correction
#> [1] FALSE
#>
#> attr(,"method")
#> [1] "Unconditional MLE & normal approximation (Wald) CI"
Created on 2024-04-06 with reprex v2.0.2