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  3. Survival Analysis in Python
  • 1

    Introduction to Survival Analysis

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    What problems does survival analysis solve, and what is censorship? You’ll answer these questions as you explore survival analysis data, build survival curves, and make basic estimations of survival time.

  • 2

    Survival Curve Estimation

    In this chapter, you’ll learn how the Kaplan-Meier model works and how to fit, visualize, and interpret it. You’ll then apply this model to explore how categorical variables affect survival and learn how to supplement your analysis using hypothesis testing methods like the log-rank test.

  • 3

    The Weibull Model

    Discover how to model time-to-event data with parametric models. Learn how to use the Weibull model and the Weibull AFT model and what different purposes they serve. Use survival regression to make inferences about how covariates affect the survival function and learn how to select the best survival model for your data.

  • 4

    The Cox PH Model

    Another chapter, another model! In this final chapter, you'll learn about the proportional hazards assumption and the role it plays in fitting and interpreting the Cox Proportional Hazards model. You’ll also learn how to predict new subjects' survival times using the Cox Proportional Hazards model.

Initializing

Ubung

Test the PH assumption with KM curves

After learning about the proportional hazards assumption, you realize that the Cox PH model you built using prison DataFrame has not been tested. You will test the proportional hazards assumption for the categorical variable fin using Kaplan-Meier curves.

cph is the fitted Cox PH model using all columns, and it has been loaded. A KaplanMeierFitter class kmf has also been instantiated.

The CoxPHFitter class, the KaplanMeierFitter class, and the matplotlib.pyplot module have been imported. The pandas and numpy libraries are imported as pd and np, respectively.

Anweisungen 1/3

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  • Fit kmf to the data of convicts that did not receive financial assistance (fin: 0).
  • Plot the survival curve of kmf and assign the plot to a variable named ax.