Survival analysis: Part I — analysis of time-to-event.

Author: Junyong IN ¹ ; Dong Kyu LEE
Author Information

1. Department of Anesthesiology and Pain Medicine, Dongguk University Ilsan Hospital, Goyang, Korea.
Publication Type:Review
Keywords: Censored data; Cox regression; Hazard ratio; Kaplan-Meier method; Log-rank test; Medical statistics; Power analysis; Proportional hazards; Sample size; Survival analysis
MeSH: Methods; Sample Size; Statistics as Topic; Survival Analysis*
From:Korean Journal of Anesthesiology 2018;71(3):182-191
CountryRepublic of Korea
Language:English
Abstract: 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.