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| Регресия на Кокс с пропорционални рискове, коригирана спрямо риска× | Тест на логаритмичните рангове за сравнение на криви на преживяемост× | |
|---|---|---|
| Област≠ | Епидемиология | Анализ на преживяемостта |
| Семейство≠ | Process / pipeline | Survival analysis |
| Година на възникване≠ | 1972 (Cox model); risk adjustment widespread from 1980s | 1966 |
| Създател≠ | D. R. Cox (base model); risk-adjustment as routine practice formalised through clinical epidemiology literature from the 1980s onward | Mantel, N. |
| Тип≠ | Multivariable survival regression | Non-parametric hypothesis test |
| Основополагащ източник≠ | Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202. DOI ↗ | Mantel, N. (1966). Evaluation of Survival Data and Two New Rank Order Statistics Arising in Its Consideration. Cancer Chemotherapy Reports, 50(3), 163–170. link ↗ |
| Други названия | adjusted Cox regression, multivariable Cox model, covariate-adjusted survival analysis, risk-adjusted survival model | Mantel log-rank test, Mantel-Cox test, log-rank sağkalım testi, Log-Rank Testi |
| Свързани≠ | 5 | 2 |
| Резюме≠ | Risk-adjusted Cox proportional hazards regression extends the classical Cox (1972) survival model by simultaneously entering known confounders — age, sex, comorbidities, disease severity — into the model alongside the exposure of primary interest. This adjustment isolates the independent effect of the exposure on the hazard of an event, producing hazard ratios (HRs) that are not distorted by baseline differences between comparison groups. It is the most widely used method for multivariable survival analysis in clinical and epidemiological research. | The log-rank test, developed by Nathan Mantel in 1966, is a non-parametric hypothesis test that compares the overall survival experience of two or more groups throughout the entire follow-up period. It is the standard companion to Kaplan-Meier curves and determines whether observed differences between curves are statistically meaningful. |
| ScholarGateНабор от данни ↗ |
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