An overview on standard statistical methods for assessing exposure-outcome link in survival analysis (Part II): the Kaplan-Meier analysis and the Cox regression method
The Kaplan-Meier and the Cox regression methods are the most used statistical techniques for performing “time to event analysis” in epidemiological and clinical research. The Kaplan-Meier analysis allows to build up one or more survival curves describing the occurrence of the outcome of interest ove...
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| Veröffentlicht in: | Aging clinical and experimental research 2012-06, Vol.24 (3), p.203-206 |
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| container_title | Aging clinical and experimental research |
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| creator | ElHafeez, Samar Abd Torino, Claudia D’Arrigo, Graziella Bolignano, Davide Provenzano, Fabio Mattace-Raso, Francesco Zoccali, Carmine Tripepi, Giovanni |
| description | The Kaplan-Meier and the Cox regression methods are the most used statistical techniques for performing “time to event analysis” in epidemiological and clinical research. The Kaplan-Meier analysis allows to build up one or more survival curves describing the occurrence of the outcome of interest over time according to the presence/absence of one or more exposures. The Cox regression method models the relationship between a specific exposure (either a continuous one like age, and systolic blood pressure or a categorical one like diabetes, degree of obesity, etc.) and the occurrence of a given outcome taking into account multiple confounders and/or predictors. |
| doi_str_mv | 10.1007/BF03325249 |
| format | Article |
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| subjects | Geriatrics/Gerontology Humans Kaplan-Meier Estimate Medicine Medicine & Public Health Outcome Assessment (Health Care) Proportional Hazards Models Regression Analysis Review Article Survival Analysis Time Factors |
| title | An overview on standard statistical methods for assessing exposure-outcome link in survival analysis (Part II): the Kaplan-Meier analysis and the Cox regression method |
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