Timeline for Causal inference for intervention with no data in pre-intervention period
Current License: CC BY-SA 4.0
8 events
| when toggle format | what | by | license | comment | |
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| May 14, 2023 at 6:53 | comment | added | ehudk | @Iterator516, unfortunately yes. Confounders should cause the treatment and outcome and therefore they must precede both. You will need unreasonable assumptions to claim post-treatment variables can be valid confounders. Moreover, adjusting for post-treatment factors usually only creates more bias since you might adjust on a mediator or a collider. | |
| May 11, 2023 at 14:09 | comment | added | Iterator516 | I have edited my question to specify that the data for confounders are available in ONLY the post-intervention period. Does that change your comment, @ehudk? | |
| May 11, 2023 at 14:08 | history | edited | Iterator516 | CC BY-SA 4.0 |
emphasized that data about confounders are in post-intervention only
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| May 11, 2023 at 7:10 | comment | added | ehudk | So I understand you just don't have outcome (sales) at baseline. That should be ok for a randomized controlled experiment. Might be less statistically efficient (including outcome pre-treatment can account for lots of the variance in outcome post-treatment and therefore make the treatment effect estimation more precise), but that's not necessary for unbiased effect estimation. | |
| May 9, 2023 at 21:10 | answer | added | dcoy | timeline score: 1 | |
| May 8, 2023 at 13:36 | comment | added | Iterator516 | Yes they are. Assume "nice" numbers and "good" conditions for everything. I'm trying to pinpoint the problem to JUST the lack of pre-intervention data. | |
| May 8, 2023 at 5:09 | comment | added | Demetri Pananos | Are these 100 stores randomly selected? | |
| May 8, 2023 at 3:56 | history | asked | Iterator516 | CC BY-SA 4.0 |