Linganisha mbinu

	Uchambuzi wa Hatari Zinazoshindana Katika Vituo Vingi	Mfumo wa Cox Proportional Hazards
Nyanja	Epidemiolojia	Epidemiolojia
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	1999 (Fine-Gray); extended to multicenter settings throughout 2000s–2010s	1972
Mwanzilishi	Fine & Gray (subdistribution hazard model); Prentice et al. (cause-specific hazard model)	Sir David Roxbee Cox
Aina	Survival / time-to-event statistical analysis	Semi-parametric regression model
Chanzo asilia	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.	Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202.
Majina mbadala	multicenter CRA, multi-site competing risks, multicenter cumulative incidence analysis, polycentric competing risks study	Cox regression, Cox PH model, proportional hazards model, CPH
Zinazohusiana	4	5
Muhtasari	Multicenter competing risks analysis is a time-to-event method applied across multiple clinical centers to estimate the probability of a specific event of interest when other mutually exclusive events — competing risks — can preclude its occurrence. By pooling data from diverse sites, it achieves the sample sizes needed to model rare events and enables assessment of center-level variation in cumulative incidence and covariate effects.	The Cox proportional hazards model is a semi-parametric regression method that estimates the effect of one or more covariates on the hazard — the instantaneous rate of an event such as death, relapse, or failure — while making no assumption about the shape of the baseline hazard function. Introduced by David Cox in 1972, it is the dominant tool for multivariable survival analysis in clinical and epidemiological research.