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Survival Analysis in Python

Shae Wang

Senior Data Scientist at Ripple

Why survival analysis?

Use cases

  • Estimate time to event
  • Measure how factors affect time to event

Censoring censoring

Survival Analysis in Python

Estimate survival curves

Kaplan-Meier estimator

  • Non-parametric model km curves

Weibull model

  • Parametric model weibull curve
Survival Analysis in Python

The lifelines package

Kaplan-Meier estimator

from lifelines import KaplanMeierFitter

kmf = KaplanMeierFitter()

kmf.fit()

Weibull model

from lifelines import WeibullFitter

wb = WeibullFitter()
wb.fit()
Survival Analysis in Python

Survival curve with covariates

Methods

  • Log-rank test
  • Weibull model
  • Cox Proportional-Hazards (Cox PH) model
Survival Analysis in Python

Thank you!

Survival Analysis in Python

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