Generalized Pairwise Comparisons
Implementation of the Generalized Pairwise Comparisons (GPC)
as defined in Buyse (2010) for complete observations,
and extended in Peron (2018) to deal with right-censoring.
GPC compare two groups of observations (intervention vs. control group)
regarding several prioritized endpoints to estimate the probability that a random observation drawn from
one group performs better than a random observation drawn from the other group.
The net benefit and win ratio statistics,
i.e. the difference and ratio between the probabilities relative to the intervention and control groups,
can then be estimated. Confidence intervals and p-values are obtained using permutations, a non-parametric bootstrap, or the asymptotic theory.
The software enables the use of thresholds of minimal importance difference,
stratification, non-prioritized endpoints (O'Brien test), and corrections to deal with missing values.