surv2sample: two-sample tests for survival analysis

Description

surv2sample is an R package that provides various two-sample tests for right-censored survival data. Three main areas and corresponding methods are:

• comparison of two survival distributions
  • surv2.logrank: weighted logrank tests and their combinations (max, sum)
  • surv2.neyman: Neyman's smooth test and its data-driven version
  • surv2.ks: Kolmogorov–Smirnov, Cramér–von Mises and Anderson–Darling test
• comparison of two cumulative incidence functions for competing risks data
  • cif: estimation and plotting of cumulative incidence functions
  • cif2.logrank: logrank-type test for subdistribution hazards
  • cif2.neyman: Neyman's smooth test and its data-driven version
  • cif2.ks: Kolmogorov–Smirnov test
  • cif2.int: integrated-difference test
• goodness of fit tests of the proportional rate assumption (proportional hazards or proportional odds functions in two samples)
  • proprate2: estimation based on the simplified partial likelihood
  • proprate2.ks: Kolmogorov–Smirnov test
  • proprate2.neyman: Neyman's smooth test and its data-driven version
  • proprate2.gs: Gill–Schumacher type test

Download and installation

You can install the package standardly directly from CRAN (using install.packages or R CMD INSTALL or a menu item in your GUI).

To download the package please visit its page on CRAN.

References

Adaptive Neyman's smooth tests of homogeneity of two samples of survival data [PDF, 260 kB]

J. Statist. Plann. Inference, 2009
doi:10.1016/j.jspi.2009.04.009

Smooth tests of equality of cumulative incidence functions in two samples [PDF, 408 kB]

Research Report 2197, Institute of Information Theory and Automation, Prague, 2007

Checking proportional rates in the two-sample transformation model [PDF, 257 kB]

Kybernetika, 45, 263–280, 2009