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. 2004 Oct;8(5):389-94.
doi: 10.1186/cc2955. Epub 2004 Sep 6.

Statistics review 12: survival analysis

Viv Bewick  1 , Liz Cheek, Jonathan Ball
Affiliations

Statistics review 12: survival analysis

Viv Bewick et al. Crit Care. 2004 Oct.

Abstract

This review introduces methods of analyzing data arising from studies where the response variable is the length of time taken to reach a certain end-point, often death. The Kaplan-Meier methods, log rank test and Cox's proportional hazards model are described.

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Figures

Figure 1
Figure 1
Plot of the survival curve for treatment 2.
Figure 2
Figure 2
Survival curves for the two treatment groups for the data in Table 1.
Figure 3
Figure 3
Cumulative hazard functions for the example data.
Figure 4
Figure 4
The Kaplan–Meier estimates of survival for (a) age > 65 years or ≤ 65 years, and (b) long-term oxygen therapy (LTOT) before intensive care unit admission (yes/no). The P values are for the log rank test.
See this image and copyright information in PMC

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