We implemented multiple tests based on the restricted mean survival time (RMST) for general factorial designs as described in Munko et al. (2024) <doi:10.1002/sim.10017>. Therefore, an asymptotic test, a groupwise bootstrap test, and a permutation test are incorporated with a Wald-type test statistic. The asymptotic and groupwise bootstrap test take the asymptotic exact dependence structure of the test statistics into account to gain more power. Furthermore, confidence intervals for RMST contrasts can be calculated and plotted and a stepwise extension that can improve the power of the multiple tests is available.

We implemented multiple tests based on the restricted mean time lost (RMTL) for general factorial designs as described in Munko et al. (2024) <doi:10.48550/arXiv.2409.07917>. Therefore, an asymptotic test and a permutation test are incorporated with a Wald-type test statistic. The asymptotic test takes the asymptotic exact dependence structure of the test statistics into account to gain more power. Furthermore, confidence intervals for RMTL contrasts can be calculated and plotted and a stepwise extension that can improve the power of the multiple tests is available.

Implemented are three Wald-type statistic and respective
  permuted versions for null hypotheses formulated in terms of cumulative hazard rate functions, medians and the concordance measure, respectively, in the general framework of survival factorial designs with possibly heterogeneous survival and/or censoring distributions, for crossed designs with an arbitrary number of factors and nested designs with up to three factors.
	Ditzhaus, Dobler and Pauly (2020) <doi:10.1177/0962280220980784> 
	Ditzhaus, Genuneit, Janssen, Pauly (2023) <doi:10.1111/biom.13575>
	Dobler and Pauly (2019) <doi:10.1177/0962280219831316>.

The philosophy in the package is described in Stasny (1988) <doi:10.2307/1391558> and Guti?rrez, A., Trujillo, L. & Silva, N. (2014), <ISSN:1492-0921> to estimate the gross flows under complex surveys using a Markov chain approach with non response.