For any spending function specified by the user, this
package provides corresponding boundaries for interim testing using
the adaptively weighted log-rank test developed by Yang and Prentice
(2010 <doi:10.1111/j.1541-0420.2009.01243.x>).
The package uses a re-sampling method to obtain stopping boundaries
at the interim looks.The output consists of stopping boundaries
and observed values of the test statistics at the interim looks,
along with nominal p-values defined as the probability of the test
exceeding the specific observed test statistic value or critical
value, regardless of the test behavior at other looks.
The asymptotic validity of the stopping boundaries is established
in Yang (2018 <doi:10.1002/sim.7958>).

Yang and Prentice Model with Piecewise Exponential Baseline
Distribution
person(given = "Fabio", family = "Demarqui", email = "fndemarqui@est.ufmg.br", role = c("aut", "cre"))
Semiparametric modeling of lifetime data with crossing survival curves via Yang and Prentice model with piecewise exponential baseline distribution curves. Details about the model can be found in Demarqui and Mayrink (2019) <arXiv:1910.02406>. Model fitting carried out via likelihood-based and Bayesian approaches. The package also provides point and interval estimation for the crossing survival times.
methods, Formula, Rcpp (>= 0.12.0), rstan (>= 2.18.1),
rstantools (>= 2.0.0)

Semiparametric modeling of lifetime data with crossing survival curves via Yang and Prentice model with piecewise exponential baseline distribution. Details about the model can be found in Demarqui and Mayrink (2019) <arXiv:1910.02406>. Model fitting carried out via likelihood-based and Bayesian approaches. The package also provides point and interval estimation for the crossing survival times.
methods, MASS, Formula, Rcpp (>= 0.12.0), rstan (>= 2.18.1),
rstantools (>= 2.0.0)

The Short-term and Long-term Hazard Ratio Model for Survival
Data
This package contains various inference procedures associated with a two-sample semi-parametric model that can accommodate a flexible range of hazard ratio patterns. This model contains the proportional hazards model and the proportional odds model as sub-models, and accommodates non-proportional hazards situations to the extreme of having crossing hazards and crossing survivor functions. Overall, this package has four major functions: 1) the parameter estimation, namely short-term and long-term hazard ratio parameters; 2) 95 percent and 90 percent point-wise confidence intervals and simultaneous confidence bands for the hazard ratio function; 3) p-value of the adaptive weighted log-rank test; 4) p-values of two lack-of-fit tests for the model. See the included "read_me_first.pdf" for brief instructions.