use discSurv package + logistic regression -> compare to our pipeline (e.g. same coefficients, etc.)
use misscpecified model (without covariate that has effect) and correctly specified model (with covariate with effect) to check that c-index, brier-score etc. have better values for correctly specified model
document()
to generate the docs and get the exported objectspipeline_survtoclassif
(seepipeline_survtoregr
) that uses the twoPipeOps
consesutivelypammtools::as_ped
=> to base R => we importpammtools
for now, no need to do anything further here