Survie Kaplan–Meier et log-rank
Survie censurée · médiane · table à risque · log-rank
Survie Kaplan–Meier et log-rank
Survie censurée · médiane · table à risque · log-rank
Calcul local dans ce navigateurOrdre des colonnes: subject_id, group, time, event_1_censored_0
Tableau modifiable
| subject_id | group | time | event_1_censored_0 | |
|---|---|---|---|---|
Coller CSV / TSV
Résultat
Loading chart…
| Groupe | N | Events | Censored | Median survival | Final survival |
|---|---|---|---|---|---|
| Control | 4 | 3 | 1 | 10 | 0.25 |
| Treatment | 4 | 2 | 2 | 20 | 0 |
⚠ Kaplan–Meier and log-rank assume non-informative censoring; inspect censoring patterns and prespecified endpoints.
Data requirements
Enter subject ID, group, non-negative time and event status (1=event, 0=censored).
subject_id, group, time, event_1_censored_0Review before reporting
Réservé à la recherche. Validez avec les données et le plan approuvé.
Check raw observations, excluded rows, model assumptions and study-specific acceptance criteria before using the result.
Transparent analysis
Inputs are processed locally in your browser. Review the calculation policy, limitations and verification approach before reporting a result.
Read the methodology →EVIDENCE & REVIEW
A result you can audit.
Reviewed 12 August 2026Censoring and risk-set logic review complete
Implementation check
The analysis keeps event status explicit, orders event times and displays group curves with at-risk context rather than reducing the data to a single median.
Interpretation boundary
Kaplan-Meier estimates rely on defensible time origins and censoring assumptions. Small risk sets and late-tail estimates should be interpreted cautiously; clinical decisions require validated statistical workflows.
Method references
Methods to Analyse Time-to-Event Data: The Kaplan-Meier Survival CurveIndian Journal of Anaesthesia / PMCKaplan-Meier estimation, censoring and comparison context.
Survival analysis: Part I — analysis of time-to-eventBritish Journal of Cancer / PMCInterpretation of survival functions, censoring and common limitations.
REFERENCE VALIDATION CASE
Two-subject survival steps
Kaplan–Meier product-limit estimate at each event time.
Inputs
- Two subjects at risk initially
- One event at day 2
- One event at day 4
- No censoring
Expected result
- S(0) = 1.00
- S(2) = 0.50
- S(4) = 0.00
Scope: A deterministic estimator check; inferential interpretation requires study context.
Review and correction history
12 August 2026 · Internal implementation review
Censoring and risk-set logic review complete. Formula behavior, unit handling, limitations and linked references were checked internally.
Independent reviewer: Not yet published. A name, relevant qualification, date and exact scope will appear here only after a real review is completed.
Source-informed and internally checked; independent scientific or regulatory validation is not claimed. Research use only.