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nph  

Planning and Analysing Survival Studies under Non-Proportional Hazards
View on CRAN: Click here


Download and install nph package within the R console
Install from CRAN:
install.packages("nph")

Install from Github:
library("remotes")
install_github("cran/nph")

Install by package version:
library("remotes")
install_version("nph", "2.1")



Attach the package and use:
library("nph")
Maintained by
Robin Ristl
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-08-23
Latest Update: 2022-05-16
Description:
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) . 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.
How to cite:
Robin Ristl (2019). nph: Planning and Analysing Survival Studies under Non-Proportional Hazards. R package version 2.1, https://cran.r-project.org/web/packages/nph. Accessed 25 Jun. 2026.
Previous versions and publish date:
1.9 (2019-08-23 12:50), 2.0 (2020-01-10 17:50)
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