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Capstone: Comparing survival curves

We saw from the last exercise that performance scores do have an effect on the survival probability. Now, let's take a look at the survival curve of all individuals using the Kaplan-Meier estimate and compare it to the curve of a Cox model that takes performance into account. Note that for Cox models, you can just enter the survfit() output into ggsurvplot() instead of creating the needed data frame yourself and plugging it into ggsurvplot_df().

This exercise is part of the course

Survival Analysis in R

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Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Compute Kaplan-Meier curve
km <- ___(___ ~ ___, data = ___)

# Compute Cox model
cxmod <- ___(___, data = ___)
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