Survival analysis: Part I - Analysis of time-to-event

Junyong In, Dong Kyu Lee

Research output: Contribution to journalReview articlepeer-review

10 Citations (Scopus)


Length of time is a variable often encountered during data analysis. Survival analysis provides simple, intuitive results concerning time-to-event for events of interest, which are not confined to death. This review introduces methods of analyzing time-to-event. The Kaplan-Meier survival analysis, log-rank test, and Cox proportional hazards regression modeling method are described with examples of hypothetical data.

Original languageEnglish
Pages (from-to)182-191
Number of pages10
JournalKorean journal of anesthesiology
Issue number3
Publication statusPublished - 2018 Jun


  • Censored data
  • Cox regression
  • Hazard ratio
  • Kaplan-Meier method
  • Log-rank test
  • Medical statistics
  • Power analysis
  • Proportional hazards
  • Sample size
  • Survival analysis

ASJC Scopus subject areas

  • Anesthesiology and Pain Medicine


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