Data Science, Analytics, Causal Inference, Editors Pick.
with. This is an indication that confounding is at work and the 30% number is suspect. Finally, as we learned in Part 1, we “de-confound” by calculating adjusted overall numbers. The adjustment is done by weighting the stratum-level numbers with the % of customers in the entire dataset that are in