| Original language | English |
|---|---|
| Title of host publication | International Encyclopedia of the Social & Behavioral Sciences |
| Editors | James D. Wright |
| Number of pages | 5 |
| Publisher | Elsevier Science Inc. |
| Publication date | 2015 |
| Edition | 2nd |
| Pages | 771-775 |
| ISBN (Print) | 9780080970868 |
| ISBN (Electronic) | 9780080970875 |
| DOIs | |
| Publication status | Published - 2015 |
Abstract
Survival analysis is the study of the distribution of time-to-event data, that is, the times from an initiating event to some terminal event. A distinguishing feature of survival data is the occurrence of right censoring, where the terminal event for some individuals is not observed; instead, it is only known that this event is at least later than a given point in time. This article presents a brief historical review and focuses on central statistical approaches: non- and semiparametric estimation (Kaplan-Meier, Cox regression) and hypothesis testing (log-rank). We also add brief comments on parametric models and list some important reference works.
Keywords
- Aalen additive hazards model
- Accelerated failure time model
- Censored data
- Cox regression
- Expected survival
- Kaplan-Meier estimator
- Log-rank test
- Nelson-Aalen estimator
- Poisson regression
- Time-to-event data