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Editorial
. 2018 Jun;10(6):3891-3896.
doi: 10.21037/jtd.2018.06.15.

Use of the Cox regression analysis in thoracic surgical research

Alice Brembilla  1 , Anne Olland  2   3   4 , Marc Puyraveau  1   5 , Gilbert Massard  2   3   4 , Frédéric Mauny  1   5 , Pierre-Emmanuel Falcoz  2   3   4
Affiliations
Editorial

Use of the Cox regression analysis in thoracic surgical research

Alice Brembilla et al. J Thorac Dis. 2018 Jun.
No abstract available

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Conflict of interest statement

Conflicts of Interest: The authors have no conflicts of interest to declare.

Figures

Figure 1
Figure 1
Illustration of time to event and time to censoring of 6 subjects. The red dot represents the entry of the subject in the study. The vertical blue lines indicate the start of the study and the end of the study. The subjects 1, 2 and 5 have experienced the event by the end of the study. The subject 3 has experienced the event after the end of the study: he is right-censored. The subject 4 is lost to follow-up during the study period: he is also right-censored. The subject 6 is left-censored.
Figure 2
Figure 2
Plot of overall 3-year survival.
Figure 3
Figure 3
Kaplan-Meier survival curves and log-rank test for the two groups of age.
Figure 4
Figure 4
Schoenfeld residuals plot for gender variable. The curve is a smoothing spline fit of the time varying estimates of the β, with a ±2 standard error confidence band represented by the dashed lines. In this example (gender variable), beta(t) is roughly flat and horizontal around zero. We can assume that there is no varying in time for this variable.
See this image and copyright information in PMC

References

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