EquiSurv - Modeling, Confidence Intervals and Equivalence of Survival
Curves
We provide a non-parametric and a parametric approach to
investigate the equivalence (or non-inferiority) of two
survival curves, obtained from two given datasets. The test is
based on the creation of confidence intervals at pre-specified
time points. For the non-parametric approach, the curves are
given by Kaplan-Meier curves and the variance for calculating
the confidence intervals is obtained by Greenwood's formula.
The parametric approach is based on estimating the underlying
distribution, where the user can choose between a Weibull,
Exponential, Gaussian, Logistic, Log-normal or a Log-logistic
distribution. Estimates for the variance for calculating the
confidence bands are obtained by a (parametric) bootstrap
approach. For this bootstrap censoring is assumed to be
exponentially distributed and estimates are obtained from the
datasets under consideration. All details can be found in
K.Moellenhoff and A.Tresch: Survival analysis under
non-proportional hazards: investigating non-inferiority or
equivalence in time-to-event data <arXiv:2009.06699>.
