Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Muundo wa Kuishi kwa Hali Nyingi (Multi-State Survival Model)× | Kikokotozi cha Kuishi cha Kaplan-Meier× | |
|---|---|---|
| Nyanja | Uchanganuzi wa Uhai | Uchanganuzi wa Uhai |
| Familia | Survival analysis | Survival analysis |
| Mwaka wa asili≠ | 1978 | 1958 |
| Mwanzilishi≠ | Andersen, P.K. & Keiding, N. (foundational framework); popularised by Putter, Fiocco & Geskus (2007) | Kaplan, E. L. & Meier, P. |
| Aina≠ | Semi-parametric hazard model | Non-parametric survival estimator |
| Chanzo asilia≠ | Putter, H., Fiocco, M. & Geskus, R.B. (2007). Tutorial in Biostatistics: Competing Risks and Multi-State Models. Statistics in Medicine, 26(11), 2389–2430. DOI ↗ | Kaplan, E. L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗ |
| Majina mbadala | illness-death model, multi-state transition model, Çok Durumlu Model (Multi-State / Illness-Death) | product-limit estimator, km curve, kaplan-meier sağkalım analizi |
| Zinazohusiana≠ | 4 | 2 |
| Muhtasari≠ | The multi-state model is a generalised survival framework, formalised in the work of Andersen and Keiding and brought to wide biostatistical practice by Putter, Fiocco and Geskus (2007), that models individuals moving through multiple distinct health states — for example, healthy, ill and dead — over time. A separate hazard function is estimated for each possible transition, and transition probabilities are recovered via the product-integral of the cumulative transition intensities. | The Kaplan-Meier estimator, introduced by Kaplan and Meier in 1958, is a non-parametric method that estimates the survival curve — the probability of remaining event-free over time — from right-censored time-to-event data. The log-rank test is the companion procedure used to compare survival curves between groups. |
| ScholarGateSeti ya data ↗ |
|
|