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Course Details

Course Outline
Learning Outcomes
Materials
Prior Knowledge

Course Outline

Introduction to survival data: Kaplan-Meier curves and the log-rank test
The Cox proportional hazards model: Implementation, interpretation and limitations
Residual analysis: Model checking and model comparison
Time-dependent covariates
Models: Parametric survival models using the Weibull distribution
Advanced topics: Frailty and joint modelling of longitudinal and survival data.

Learning Outcomes

By the end of the day participants will…

be able to use a Kaplan-Meier curve to estimate the survival function from lifetime data
be familiar with Cox proportional hazards models, which are used when investigating the association between predictor variables and the survival distribution
be able to cross-check different models to find the optimum, using residual analysis
have learned examples of parameterised survival models
be able to acknowledge differences between parameterised models and Cox models

Materials

Prior Knowledge

It is expected that participants have basic R experience. The course will be hands-on and applied with short introductory lectures to each topic, followed by practical sessions working with real survival datasets, available within R.

Training Course Details

Survival/Churn Analysis with R

Course Level: Intermediate