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

Junyong In, Dong Kyu Lee

    Research output: Contribution to journalReview articlepeer-review

    23 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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