Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.

The primary goal of survival analysis is to estimate survival time—the time until a specified event occurs—and to understand the factors that influence it. Key concepts include the survival function (S(t)), which gives the probability of surviving beyond a given time, and the hazard function (h(t)), which describes the instantaneous event rate at any time. These functions provide insights into survival patterns and risks over time.

Common methods include the Kaplan-Meier estimator, a non-parametric approach that generates survival curves and allows comparison of survival rates across groups, and the Cox proportional hazards model, a semi-parametric method that examines how covariates influence survival without assuming a specific distribution for survival times.

Survival analysis is extensively used in medicine to assess treatment effects and predict patient outcomes, in engineering to estimate product lifespans, and in social sciences to analyze durations like unemployment or time-to-life events. Its ability to handle censored data and model time-dependent phenomena makes it an essential tool for understanding and predicting outcomes in various fields.

From Chapter 15:

article

Now Playing

15.1 : Introduction To Survival Analysis

Survival Analysis

75 Views

article

15.2 : Life Tables

Survival Analysis

42 Views

article

15.3 : Survival Curves

Survival Analysis

36 Views

article

15.4 : Actuarial Approach

Survival Analysis

30 Views

article

15.5 : Kaplan-Meier Approach

Survival Analysis

38 Views

article

15.6 : Assumptions of Survival Analysis

Survival Analysis

32 Views

article

15.7 : Comparing the Survival Analysis of Two or More Groups

Survival Analysis

47 Views

article

15.8 : The Mantel-Cox Log-Rank Test

Survival Analysis

148 Views

article

15.9 : Applications of Life Tables

Survival Analysis

24 Views

article

15.10 : Cancer Survival Analysis

Survival Analysis

210 Views

article

15.11 : Hazard Rate

Survival Analysis

39 Views

article

15.12 : Hazard Ratio

Survival Analysis

41 Views

article

15.13 : Truncation in Survival Analysis

Survival Analysis

74 Views

article

15.14 : Censoring Survival Data

Survival Analysis

25 Views

article

15.15 : Survival Tree

Survival Analysis

26 Views

See More

JoVE Logo

Privacy

Terms of Use

Policies

Research

Education

ABOUT JoVE

Copyright © 2025 MyJoVE Corporation. All rights reserved