Closed miretchin closed 6 months ago
Hey @miretchin , you can use the alpha
parameter - by default it is set to 0.05 for the confidence intervals.
For example in the kaplan meier fitter:
from lifelines import KaplanMeierFitter
from lifelines.datasets import load_waltons
waltons = load_waltons()
kmf = KaplanMeierFitter(label="waltons_data", alpha=0.32)
kmf.fit(waltons['T'], waltons['E'])
kmf.plot()
As per the documentation, you can pass in the alpha
value on the fit method as well - and this will override the one set on the initialization of the kmf object for the current call of fit. For example, this will set it to the 68% in your question:
from lifelines import KaplanMeierFitter
from lifelines.datasets import load_waltons
waltons = load_waltons()
kmf = KaplanMeierFitter(label="waltons_data")
kmf.fit(waltons['T'], waltons['E'], alpha=0.32)
kmf.plot()
Fantastic, thank you.
Hello,
Great library. Just curious if it's possible to change the % interval of the confidence interval? It defaults to 95%, but sometimes it is advantageous to change from 95% to, say, 68%.
Thank you!