The abpackage implements PrePost, a Bayesian approach for the estimation of the treatment effect in A/B testing. When pre-period data are available, the method leverages the pre-period to get a more accurate estimate of the treatment effect.

The abpackage assumes that the observations are Normally distributed both in the pre-period and the post-period. Furthermore, the package assumes that the observations in treatment and control groups are identically distributed in the pre-period.

install.packages("devtools")
library(devtools)
devtools::install_github("google/abpackage")
library(abpackage)

Documentation and examples

Percent Change Estimation in Large Scale Online Experiments