Thank you very much for developing and maintaining this package - it has been very helpful.
I am applying HonestDiD to a Callaway–Sant’Anna dynamic event-study (with bstrap = TRUE, min_e = -4, max_e = 6). The DID event-study shows significant post-treatment effects (aggregated) with reasonably tight CIs. However, the “original CI” from HonestDiD (at M = 0) is much wider and becomes non-significant.
It seems to me that the discrepancy is because the HonestDiD by default performs the sensitivity analysis for the first period. Is there an option I can specify to perform a sensitivity analysis of the aggregated effect? I saw the example of using c(0.5, 0.5) for the average of two periods, but I'm not sure if this applies to the case of the CS estimator and how it accounts for the weights across the periods.
Thank you very much for your help.
Thank you very much for developing and maintaining this package - it has been very helpful.
I am applying HonestDiD to a Callaway–Sant’Anna dynamic event-study (with bstrap = TRUE, min_e = -4, max_e = 6). The DID event-study shows significant post-treatment effects (aggregated) with reasonably tight CIs. However, the “original CI” from HonestDiD (at M = 0) is much wider and becomes non-significant.
It seems to me that the discrepancy is because the HonestDiD by default performs the sensitivity analysis for the first period. Is there an option I can specify to perform a sensitivity analysis of the aggregated effect? I saw the example of using c(0.5, 0.5) for the average of two periods, but I'm not sure if this applies to the case of the CS estimator and how it accounts for the weights across the periods.
Thank you very much for your help.