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| Visszatekintő túlélés-elemzés× | Cox Proporcionális Kockázat× | |
|---|---|---|
| Tudományterület | Epidemiológia | Epidemiológia |
| Módszercsalád | Process / pipeline | Process / pipeline |
| Keletkezés éve≠ | 1970s–1980s (retrospective variant established) | 1972 |
| Megalkotó≠ | Kaplan & Meier (foundational estimator, 1958); Cox (regression model, 1972); retrospective application is a design variant documented since the 1970s | Sir David Roxbee Cox |
| Típus≠ | Retrospective observational analytical study | Semi-parametric regression model |
| Alapmű≠ | Collett, D. (2015). Modelling Survival Data in Medical Research (3rd ed.). CRC Press. ISBN: 978-1439856789 | Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202. DOI ↗ |
| Alternatív nevek | historical survival study, retrospective time-to-event analysis, retrospective follow-up survival study, archival survival analysis | Cox regression, Cox PH model, proportional hazards model, CPH |
| Kapcsolódó | 5 | 5 |
| Összefoglaló≠ | Retrospective survival analysis applies time-to-event statistical methods — most commonly the Kaplan-Meier estimator and Cox proportional hazards regression — to data collected from past records rather than through prospective follow-up. The researcher looks back at medical records, disease registries, or administrative databases to reconstruct each patient's journey from a defined starting point (e.g., diagnosis or surgery) to an outcome of interest (e.g., death, relapse, or hospital readmission), making it a cost-efficient approach for studying prognosis and risk factors when prospective follow-up is not feasible. | 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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