Implementation for time-varying survival analysis

[felipe0216]

Hello,

Thanks for all the good work put into this package, it is definitely a big contribution to the community. I am currently looking into this package to model moving dates in a real state context.

I wanted to know about the time-varying implementation of the RDSM model. Currently working with time series data and time to event, so I wanted to know what are the caviats that we need to keep in mind when implementing the RDSM in comparison to the baseline DSM. Are there any particular steps that we need to be careful of during the pre-processing (apart from the obvious expanded dataset) such as high dimensionality, categorical variables, missing values or any other ?

For anyone wondering about the time-varying implementation, there is an example added: https://github.com/autonlab/auton-survival/blob/master/examples/RDSM%20on%20PBC%20Dataset.ipynb

and a publication: http://proceedings.mlr.press/v146/nagpal21a/nagpal21a.pdf

[chiragnagpal]

High @felipe0216 thank you for you kind words :) One thing I would mention is that when preprocessing data for time-varying survival regression, you would need to be careful about how to handle missing data. In particular, it would not be logical correct to impute missing data based on the future observations for that individual. So one would have to be a little careful about such things.