"Propensity score matching entails forming matched sets of treated and untreated subjects who share a similar value of the propensity score. Once a matched sample has been formed, the treatment effect can be estimated by directly comparing outcomes."
"To put it simply, this is an additional A/B tests technique employed when sample randomisation doesn't work. Propensity score is counted for every user and matched with another user based on historical data."
"In some cases it's not possible to employ an A/B platform with a built-in splitting function. Possible cases include the high cost and time required for A/B testing implementation."
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