nph: Planning and Analysing Survival Studies under Non-Proportional Hazards

Piecewise constant hazard functions are used to flexibly model survival distributions with non-proportional hazards and to simulate data from the specified distributions. A function to calculate weighted log-rank tests for the comparison of two hazard functions is included. Also, a function to calculate a test using the maximum of a set of test statistics from weighted log-rank tests (MaxCombo test) is provided. This test utilizes the asymptotic multivariate normal joint distribution of the separate test statistics. The correlation is estimated from the data. These methods are described in Ristl et al. (2021) <doi:10.1002/pst.2062>. Finally, a function is provided for the estimation and inferential statistics of various parameters that quantify the difference between two survival curves. Eligible parameters are differences in survival probabilities, log survival probabilities, complementary log log (cloglog) transformed survival probabilities, quantiles of the survival functions, log transformed quantiles, restricted mean survival times, as well as an average hazard ratio, the Cox model score statistic (logrank statistic), and the Cox-model hazard ratio. Adjustments for multiple testing and simultaneous confidence intervals are calculated using a multivariate normal approximation to the set of selected parameters.

Package details

AuthorRobin Ristl [aut, cre], Nicolas Ballarini [ctb]
MaintainerRobin Ristl <>
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the nph package in your browser

Any scripts or data that you put into this service are public.

nph documentation built on May 17, 2022, 1:06 a.m.