Simultaneous confidence bands for Cox regression from semiparametric random censorship

Shoubhik Mondal, Sundarraman Subramanian

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


Cox regression is combined with semiparametric random censorship models to construct simultaneous confidence bands (SCBs) for subject-specific survival curves. Simulation results are presented to compare the performance of the proposed SCBs with the SCBs that are based only on standard Cox. The new SCBs provide correct empirical coverage and are more informative. The proposed SCBs are illustrated with two real examples. An extension to handle missing censoring indicators is also outlined.

Original languageEnglish (US)
Pages (from-to)122-144
Number of pages23
JournalLifetime Data Analysis
Issue number1
StatePublished - Jan 1 2016

All Science Journal Classification (ASJC) codes

  • Applied Mathematics


  • Counting process
  • Empirical coverage
  • Equal-precision
  • Gaussian multiplier bootstrap
  • Martingale
  • Strong consistency


Dive into the research topics of 'Simultaneous confidence bands for Cox regression from semiparametric random censorship'. Together they form a unique fingerprint.

Cite this