Linganisha mbinu

	Uchambuzi wa Meta-uchambuzi wa Usalama wa Maisha	Mfumo wa Cox Proportional Hazards
Nyanja	Epidemiolojia	Epidemiolojia
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	1990s–2000s (formalized ~1998)	1972
Mwanzilishi	Parmar, Torri & Stewart (statistical framework); broader IPD tradition developed by the Early Breast Cancer Trialists' Collaborative Group	Sir David Roxbee Cox
Aina	Quantitative synthesis / meta-analytic method	Semi-parametric regression model
Chanzo asilia	Parmar, M. K. B., Torri, V., & Stewart, L. (1998). Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints. Statistics in Medicine, 17(24), 2815–2834.	Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202.
Majina mbadala	meta-analysis of time-to-event data, pooled survival analysis, IPD survival meta-analysis, aggregate survival meta-analysis	Cox regression, Cox PH model, proportional hazards model, CPH
Zinazohusiana	4	5
Muhtasari	Meta-analytic survival analysis is a quantitative synthesis method that pools hazard ratios and related time-to-event statistics from multiple independent studies to produce a single, more precise estimate of a treatment or exposure effect on survival outcomes such as overall survival, disease-free survival, or time to relapse. It can operate on aggregate published data or on individual patient data (IPD) contributed directly by study investigators.	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.