Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Meta-analytic Cox Proportional Hazards× | Mfumo wa Cox Proportional Hazards× | |
|---|---|---|
| Nyanja | Epidemiolojia | Epidemiolojia |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 1998–2007 | 1972 |
| Mwanzilishi≠ | Parmar, Torri & Stewart; Tierney et al. | Sir David Roxbee Cox |
| Aina≠ | Meta-analytic survival model | Semi-parametric regression model |
| Chanzo asilia≠ | Tierney, J. F., Stewart, L. A., Ghersi, D., Burdett, S., & Sydes, M. R. (2007). Practical methods for incorporating summary time-to-event data into meta-analysis. Trials, 8(1), 16. DOI ↗ | Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202. DOI ↗ |
| Majina mbadala | pooled Cox regression meta-analysis, meta-Cox model, survival meta-analysis, Cox PH pooling | Cox regression, Cox PH model, proportional hazards model, CPH |
| Zinazohusiana≠ | 3 | 5 |
| Muhtasari≠ | Meta-analytic Cox proportional hazards is a quantitative synthesis technique that pools log hazard ratios from multiple Cox regression survival analyses into a single, more precise estimate of the association between an exposure or treatment and a time-to-event outcome. It combines the inferential power of survival analysis with the evidence-aggregation logic of meta-analysis, making it the standard approach for summarising multi-study survival evidence in clinical and epidemiological research. | 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. |
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