2012-11-15
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
Publication
Publication
Aging Clinical and Experimental Research , Volume 24 - Issue 3 p. 203- 206
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.
Additional Metadata | |
---|---|
, , | |
hdl.handle.net/1765/91030 | |
Aging Clinical and Experimental Research | |
Organisation | Department of Internal Medicine |
Elhafeez, S. A., Torino, C., D'Arrigo, G., Bolignano, D., Provenzano, F., Mattace Raso, F., … Tripepi, G. (2012). 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. Aging Clinical and Experimental Research (Vol. 24, pp. 203–206). Retrieved from http://hdl.handle.net/1765/91030 |