SURV4CR
Survival Analysis for Clinical Research with R
SURV4CR
Survival Analysis for Clinical Research with RTime-to-event
Course description
SURV4CR provides a practical and methodologically rigorous introduction to survival analysis for clinical research using R. It covers the full time-to-event analysis workflow: survival data structure, censoring, Kaplan-Meier estimation, log-rank tests, Cox regression, proportional hazards diagnostics, competing risks, RMST, survival machine learning, dynamic RMST analysis, and temporal phenotyping.
The course emphasizes clinical interpretation, correct handling of censoring, model assumptions, reproducible analysis, and responsible use of machine learning for time-to-event outcomes.
Learning objectives
By the end of SURV4CR, participants will be able to:
- define time origin, event, follow-up time, and censoring mechanism;
- structure survival data using R;
- estimate and interpret Kaplan-Meier curves and perform log-rank tests;
- fit and assess Cox proportional hazards models, including diagnostics and extensions;
- analyze competing risks using cumulative incidence and Fine-Gray models;
- use RMST as a clinically interpretable survival estimand;
- fit, evaluate, and interpret survival machine learning models;
- compute dynamic RMST curves and apply temporal clustering for survival phenotyping;
- produce a reproducible survival analysis report.
Schedule
| No. | Topic |
|---|---|
| 1 | Survival data structure, study design & Kaplan-Meier/log-rank |
| 2 | Cox proportional hazards model |
| 3 | Cox model extensions (stratified, time-varying, frailty) |
| 4 | Competing risks and flexible parametric models |
| 5 | RMST as a clinical estimand |
| 6 | Survival ML: foundations, evaluation & tuning |
| 7 | Survival ML interpretation, dynamic RMST & temporal phenotyping |
| 8 | End-to-end survival analysis project |
Practical information
- Audience
- Clinicians, clinical researchers, epidemiologists, PhD students, analysts with follow-up data
- Prerequisites
- Basic R and regression recommended, as covered in BIOSTATR
- Format
- Live sessions, slides, notebooks, datasets, exercises
- Schedule
- Mon/Wed/Fri 18h00–20h00, Sun 10h00–12h00 (Morocco time)
- Tools
- R, RStudio, Quarto
- Assessment
- Reproducible Quarto mini-project
- Next step
- METAR