A/B testing, also known as Split Testing, is the technique of determining if there is a statistically significant difference in the outcomes of control and test groups. But the two groups might not be normal and might not be homogeneous, hence we have to test for normality and homogenity first, then apply a suitable statistical test.
The idea behind Double Regression is to perform multiple and separate regressions on the effect of Confounders and Instrumental variable (e401) on Target variable (net_tfa), the effect of Confounders and Instrumental variable on Control variable (p401), and the effects of Confounders on Instrumental variable.
Introduction
Causal Analysis is the study of causation as opposed to correlation. Given two events A and B which appear to be correlated, can we determine with a certain statistical significance if one of them is the cause of another?