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 Clin Exp Res. 2012 Jun;24(3):203-6. doi: 10.1007/BF03325249.

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.

Publication types

  • Review

MeSH terms

  • Humans
  • Kaplan-Meier Estimate*
  • Outcome Assessment, Health Care*
  • Proportional Hazards Models*
  • Regression Analysis
  • Survival Analysis*
  • Time Factors