- [[230222_171403 compare campaigns|compare covariates across campaigns]] # interact treatment effect with extra covariate `t0propSC` (proportion active days before campaign) Pre-campaign proportion of days with at least 1 tweet/retweet/quote/reply. The `t0prop` variable is very very skewed and hard to make it normal - applied `sqrt` transform and then median-centered it (`t0propSC`). The skewness makes the `conditionC` simple effect harder to interpret (since estimates depend on how we center the covariates). See `conditionC:t0propSC` effects below. Mixed evidence. - exp1 and exp2: negative interaction?? (treatment worked better for users with higher t0 activity) - exp3 and exp4: positive interaction?? (treatment was less effective for users with higher t0 activity) ## exp1 pilot ![[_count_winsorize-0.95-clustse 9.png]] ![[_sum_winsorize-0.95-clustse 9.png]] ## exp2 deepstate ![[count-winsorize-0.95-clustse 15.png]] ![[frac-winsorize-0.95-clustse 13.png]] ![[sum-winsorize-0.95-clustse 16.png]] ## exp3 trucker ![[count-winsorize-0.95-clustse 17.png]] ![[frac-winsorize-0.95-clustse 15.png]] ![[sum-winsorize-0.95-clustse 18.png]] ## exp4 deepstate ![[count-winsorize-0.95-clustse 18.png]] ![[frac-winsorize-0.95-clustse 16.png]] ![[sum-winsorize-0.95-clustse 19.png]]