The E-learning system for the cluster statistical modeling (II) is focused on survival analysis. Two courses are available: Introduction to Survival analysis using R (Developed by Roel Braekers with R examples of Alessio Crippa) and Survival analysis using R (developed by David Harrington).
- Introduction to Survival analysis using R (See Survival analysis I).
The course covers the following topics in survival analysis:
- Censoring.
- Estimation of the survival function.
- Life tables and Kaplan-Meier estimator.
- Comparison of survival curves.
- Test for two or more samples.
- Log-rank test, tests for trend and stratified tests.
- Cox’s regression model and stratifed proportional hazards.
- Time-dependent covariates.
- Survival distributions and parametric regression models in survival analysis.
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Accelerated failure time regression models
- Survival Analysis using R (See Survival analysis II).
The course covers the following topics in survival analysis:
- Introduction and background.
- Non-parametric estimation of a survival distribution.
- Significance tests with censored data.
- Proportional hazards regression: basics.
- Proportional hazards regression: special topics.
- Designing a survival study.