Core - Statistics

Chapter 15

Survival Analysis

15.1 : Introduction To Survival Analysis

15.1 : Introduction To Survival Analysis

Consider the following three examples from biomedical studies. First, in cancer research, the time from when a patient enters remission to their relapse ...

15.2 : Life Tables

15.2 : Life Tables

A life table or a mortality table represents the survival patterns of a population. It comprises multiple columns, each serving a practical purpose, ...

15.3 : Survival Curves

15.3 : Survival Curves

Consider a graph of the cumulative probability of death plotted as age on the X axis versus the proportion dead on the Y axis for a specific year. This ...

15.4 : Actuarial Approach

15.4 : Actuarial Approach

Survival analysis assesses the time until an event such as death or treatment failure occurs. The actuarial or life table approach, adapted from actuarial ...

15.5 : Kaplan-Meier Approach

15.5 : Kaplan-Meier Approach

The Kaplan-Meier estimator estimates the survival function from lifetime data. It is primarily used in medical research to track patient survival after ...

15.6 : Assumptions of Survival Analysis

15.6 : Assumptions of Survival Analysis

Survival analysis, a statistical method, evaluates the time until an event occurs. It is commonly used in medicine to analyze life expectancy. It is ...

15.7 : Comparing the Survival Analysis of Two or More Groups

15.7 : Comparing the Survival Analysis of Two or More Groups

Survival analysis evaluates the time until an event, like disease recurrence or death, utilizing techniques that account for censored data, where the ...

15.8 : The Mantel-Cox Log-Rank Test

15.8 : The Mantel-Cox Log-Rank Test

The Mantel-Cox log-rank test is a nonparametric statistical method for comparing survival distribution curves between two groups. It is typically employed ...

15.9 : Applications of Life Tables

15.9 : Applications of Life Tables

A life table, or mortality table, is a statistical tool that compiles a population's mortality characteristics, providing survival and death ...

15.10 : Cancer Survival Analysis

15.10 : Cancer Survival Analysis

Cancer survival analysis measures the time from diagnosis or start of the treatment to an event like recurrence or death. This analysis is crucial for ...

15.11 : Hazard Rate

15.11 : Hazard Rate

In a clinical study, the subjects or participants are observed over a time interval for an event, such as death, that occurs only once. Now, if a ...

15.12 : Hazard Ratio

15.12 : Hazard Ratio

The hazard ratio compares the hazard or risk of an event occurring at any given point in time between two groups. Consider λ(t) as a hazard rate at ...

15.13 : Truncation in Survival Analysis

15.13 : Truncation in Survival Analysis

In survival analysis, time is measured from the study start, ensuring all participants are observed from time zero until they die or are censored. But, ...

15.14 : Censoring Survival Data

15.14 : Censoring Survival Data

In survival data, censoring leads to incomplete data, and it typically occurs when subjects experience an event before or after the study ends. ...

15.15 : Survival Tree

15.15 : Survival Tree

A survival tree is used to model and visualize the relationship between a set of covariates and the time until an event of interest occurs. It is ...

15.16 : Parametric Survival Analysis: Weibull and Exponential Methods

15.16 : Parametric Survival Analysis: Weibull and Exponential Methods

Weibull and exponential models are frequently used in survival analysis. A two-parameter Weibull distribution has a survival curve given as follows. Here, ...

Copyright © 2025 MyJoVE Corporation. All rights reserved

We use cookies to enhance your experience on our website.

By continuing to use our website or clicking “Continue”, you are agreeing to accept our cookies.

Learn More