विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| सर्वाइवल रिग्रेशन (Survival Regression)× | कॉक्स प्रोपोर्शनल हैज़र्ड्स रिग्रेशन× | कैप्लान-मेयर सर्वाइवल एस्टिमेटर× | |
|---|---|---|---|
| क्षेत्र≠ | सांख्यिकी | उत्तरजीविता | उत्तरजीविता |
| परिवार≠ | Regression model | Survival analysis | Survival analysis |
| उद्भव वर्ष≠ | 1980s | 1972 | 1958 |
| प्रवर्तक≠ | Kalbfleisch & Prentice; Cox & Oakes | Cox, D. R. | Kaplan, E. L. & Meier, P. |
| प्रकार≠ | Parametric survival model | Semi-parametric hazard regression model | Non-parametric survival estimator |
| मौलिक स्रोत≠ | Kalbfleisch, J. D., & Prentice, R. L. (2002). The Statistical Analysis of Failure Time Data (2nd ed.). Wiley. ISBN: 978-0471363576 | Cox, D. R. (1972). Regression Models and Life-Tables. Journal of the Royal Statistical Society: Series B, 34(2), 187–202. DOI ↗ | Kaplan, E. L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗ |
| उपनाम≠ | accelerated failure time model, AFT model, parametric survival model, time-to-event regression | cox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonu | product-limit estimator, km curve, kaplan-meier sağkalım analizi |
| संबंधित≠ | 3 | 3 | 2 |
| सारांश≠ | Survival regression models the time until an event occurs — such as death, failure, or relapse — as a function of covariates. Unlike ordinary regression, it properly accounts for censored observations (cases where the event had not yet occurred at the end of follow-up) by specifying a parametric distribution for the survival time and estimating covariate effects via maximum likelihood. | Cox proportional hazards regression, introduced by D. R. Cox in 1972, is a semi-parametric model that estimates how one or more covariates affect the hazard — the instantaneous rate of experiencing an event — while leaving the baseline hazard function unspecified. It is the standard multivariable method in survival analysis and produces hazard ratios that quantify the relative risk associated with each predictor. | The Kaplan-Meier estimator, introduced by Kaplan and Meier in 1958, is a non-parametric method that estimates the survival curve — the probability of remaining event-free over time — from right-censored time-to-event data. The log-rank test is the companion procedure used to compare survival curves between groups. |
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