Linganisha mbinu

	Muundo wa Kuishi kwa Hali Nyingi (Multi-State Survival Model)	Uchanganuzi wa Kunusurika kwa Matukio Yanayoshindana
Nyanja	Uchanganuzi wa Uhai	Uchanganuzi wa Uhai
Familia	Survival analysis	Survival analysis
Mwaka wa asili	1978	1999
Mwanzilishi	Andersen, P.K. & Keiding, N. (foundational framework); popularised by Putter, Fiocco & Geskus (2007)	Fine, J.P. & Gray, R.J.
Aina	Semi-parametric hazard model	Competing risks survival model
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.	Fine, J.P. & Gray, R.J. (1999). A Proportional Hazards Model for the Subdistribution of a Competing Risk. Journal of the American Statistical Association, 94(446), 496–509.
Majina mbadala	illness-death model, multi-state transition model, Çok Durumlu Model (Multi-State / Illness-Death)	Rekabet Eden Riskler Analizi, cumulative incidence function, CIF analysis, cause-specific survival analysis
Zinazohusiana	4	5
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.	Competing risks analysis, formalized by Fine and Gray in 1999, is a survival analysis framework for settings where a subject can experience one of several mutually exclusive event types. The key quantity is the cumulative incidence function (CIF), which estimates the probability of a specific event occurring by time t in the presence of the other competing events.