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. ©2012, Editrice Kurtis.

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

Bolignano D.;
2012-01-01

Abstract

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. ©2012, Editrice Kurtis.
2012
Cox regression analysis; Kaplan-Meier analysis; Survival analysis; Humans; Regression Analysis; Time Factors; Kaplan-Meier Estimate; Outcome Assessment, Health Care; Proportional Hazards Models; Survival Analysis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12317/59786
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