I agree that “observational causal inference through regression” rests on fairly incredible model assumptions – no unmeasured confounders being the most problematic one!
That said, I think it is still possible to draw meaningful inferences from observational data under more credible model assumptions that include the possible influence of unmeasured confounders. See for instance: https://openreview.net/pdf?id=XnYtGPgG9p
Hi Ben,
I agree that “observational causal inference through regression” rests on fairly incredible model assumptions – no unmeasured confounders being the most problematic one!
That said, I think it is still possible to draw meaningful inferences from observational data under more credible model assumptions that include the possible influence of unmeasured confounders. See for instance: https://openreview.net/pdf?id=XnYtGPgG9p
Thanks, Dave. I'll take a look! The course moves to reinforcement learning next week, so stay tuned...
Looking forward to it!