PhD / Research · Biostatistics and Data Science

Survival analysis

Time-to-event analysis handles outcome timing and censored follow-up. It is used when observation periods differ or not every participant experiences the event.

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Survival analysis — learning map

Original conceptual SVG · scalable
LABELED RELATIONSHIP MAP · SCHEMATIC, NOT TO SCALETime origin and eventdefine clearlyCensoringincomplete event timesKaplan–Meier estimationestimate survival functionCox proportional hazardscovariate associationSurvival analysisKEY RELATIONSHIPS

Original schematic relationship map for this topic; relationships are organized for study, not intended as an anatomical depiction or a diagnostic algorithm.

Concept 01

Time origin and event

Specify entry, event definition, competing events and what constitutes the end of observation before analysis.

Concept 02

Censoring

Right censoring means the event has not been observed before follow-up ends; valid inference depends on assumptions about the censoring process.

Concept 03

Kaplan–Meier estimation

A product-limit estimator summarizes the probability of remaining event-free across observed event times, under suitable assumptions.

Concept 04

Cox proportional hazards

A Cox model relates predictors to the hazard; proportionality and event definitions should be assessed before interpreting the hazard ratio.

Education / safety note: A hazard ratio is not a direct ratio of probabilities at a fixed time, and competing risks may require alternative methods.

Reference and next reading

Explore the original curriculum and publisher-hosted resources for full-depth reading; this note is an original schematic introduction, not an exhaustive chapter.

Official / publisher source: PubMed ↗Official / publisher source: PubMed ↗Official / publisher source: PubMed ↗