AIPW for survival analysis ?

[JUNGYO]

Theoretical background of AIPTW is interesting, but can I use this "weight" for survival analysis? (like, Cox regression)
Sorry for my lack of understanding on statistics.

[pzivich]

Unfortunately the implemented AIPW is not ready for survival data. Briefly, AIPW works by combining the IPW with the predicted outcomes values (from g-computation). The formula that combines the two leads to all the wonderful AIPW properties. So right now, AIPTW takes exposures and outcomes as input. There is no option to keep track of time, so it won't work as expected for survival data.

While not yet implemented, Longitudinal AIPW and Longitudinal TMLE (this is in the works but I have't worked on it recently) could technically be applied to this problem. You would divide the survival data into equally-sized checks of time, then use those algorithms. This is common practice for time-varying confounding. But like I said, these are not yet implemented but are on the short list.

However, you can use SurvivalGFormula to compare with your IPW results. HERE are some reference documentations. While AIPW doesn't exist a comparison between the IPW and g-formula results would help to catch obvious instances of model misspecification.