I am trying to fit a parametric survival regression for a dataset that I have, I wanted to understand the interpretation of the output of the lifeline package for the lognormal AFT model I have built. I have dummified the features and have fit the model like below:
lnf = LogNormalAFTFitter().fit(data_train, 'durations', event_col='events')
The results are as below. I'm trying to understand 1. What are the important features, How much each feature increases or decreases the survival time, 2. How can I calculate cumulative hazard for each row in my table
I am confused as to whether the coefficients determine the survival time or hazard ratio?