Cracking time's code: Survival analysis of large datasets¶
Welcome to this ReCoDE project!
Description of the project¶
This is a special type of analysis that takes into consideration when the event occurred rather than if the event occurred. In other words, we are focused on knowing the rate, which is the number of events per unit time.
In this exemplar will introduce you to the concept of survival analysis (also known as a time-to-event analysis) using large datasets using R for both unadjusted and adjusted models.
A common timescale used in survival analysis is time-to-event, however in large cohort studies data may be left-truncated (participants entering the study at different time points), making the time-scale unsuitable. Instead, age should be considered as the timescale. This is most relevant when exploring age-dependent associations between exposures and outcomes.
Learning Outcomes¶
- Understand the different types of censoring and how to curate your data
- Conduct univariable and multivariable survival analysis using R
- Graphically present the findings of a survival analysis
- Interprete the results from a survival analysis
| Task | Time |
|---|---|
| Pre-session material | 3 hours |
| Data curation | 2 hours |
| Analysis | 2 hours |
| Visualisation & Interpretation of results | 2 hours |
What steps should you follow when completing this examplar?¶
- Start by reading the ReCoDE main page.
- Complete the
Introductionsection (video lecture, reading materials) - Continue with
Data Curation(get your data ready for a survival analysis) - Conduct a
Survival analysis(unadjusted and adjusted) - Take your analysis to the next level by attempting the extension task
Advanced survival analysis(analysis using different types of death)
Finally I hope you enjoy and learn from this ReCoDE project!
License¶
This project is licensed under the BSD-3-Clause license