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This is a Quantitative Study study.

October 2, 2025Open Access

Subset Selection for Stratified Sampling in Online Controlled Experiments

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This approach improves statistical power and reduces variance in online controlled experiments, suggesting better marketing decisions.

Using subset selection can enhance sensitivity in online controlled experiments, improving marketing effectiveness.
The algorithm efficiently selects stratification variables, leading to reduced variance and more reliable outcomes.
Our method outperforms other variance reduction techniques, particularly with correlated variables affecting outcomes.
Computational experiments support the effectiveness of this approach, underscoring its potential for digital marketing strategies.

Momozu et al. (2025) studied this question.

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