# Survival analysis: An introduction to concepts, methods & software

Survival (or time-to-event) analysis is used to analyse data such as the failure of a mechanical component, the onset of a disease, or the death of an organism. This free introductory course will provide you with an in-depth introduction to the core concepts, methods and software needed to start your journey into the world of survival analysis.

### Lectures

1. Basic concepts in survival analysis
2. Time-at-risk
3. Timescales
4. Censoring
5. Survival analysis using Stata
6. Rates
7. Survival, Kaplan-Meier, and comparing survival
8. Hazard and cumulative hazard
9. Parametric survival models
10. Cox model
11. The proportional hazards assumption
12. Allowing for non-proportional hazards

### Practicals

1. Survival data
2. Modelling survival data
3. Assessing proportional hazards
4. Modelling non-proportional hazards

Videos

### State-of-the-art statistical models for modern HTA

At @RedDoorAnalytics, we develop methodology and software for efficient modelling of biomarkers, measured repeatedly over time, jointly with survival outcomes, which are being increasingly used in cancer settings. We have also developed methods and software for general non-Markov multi-state survival analysis, allowing for the development of more plausible natural history models, where patient history can […]

Videos

### Multilevel (hierarchical) survival models: Estimation, prediction, interpretation

Hierarchical time-to-event data is common across various research domains. In the medical field, for instance, patients are often nested within hospitals and regions, while in education, students are nested within schools. In these settings, the outcome is typically measured at the individual level, with covariates recorded at any level of the hierarchy. This hierarchical structure […]

Statistical Primers

### What are competing risks?

Competing risks In survival analysis, competing risks refer to the situation when an individual is at risk of experiencing an event that precludes the event under study to occur. Competing risks commonly occur in studies of cause-specific mortality, as all other causes of death than the one under study might happen before the individuals “have […]