Articles on early stopping

Q&A on Sequential Statistics in A/B Testing

Sequential testing QA

Sequential statistics are gathering interest and there are more and more questions posed by CROs looking into the matter. For this article I teamed up with Lucia van den Brink, a distinguished CRO consultant who recently started using Analytics Toolkit and integrated frequentist sequential testing into her client workflow. In this short interview she asks […] Read more…

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Futility Stopping Rules in AGILE A/B Testing

Stopping for Lack of Effect (Futility)

In this article we continue our examination of the AGILE statistical approach to AB testing with a more in-depth look into futility stopping, or stopping early for lack of positive effect (lack of superiority). We’ll cover why such rules are helpful and how they help boost the ROI of A/B testing, why a rigorous statistical rule […] Read more…

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Efficient AB Testing with the AGILE Statistical Method

AGILE AB Testing

Don’t we all want to run tests as quickly as possible, reaching results as conclusive and as certain as possible? Don’t we all want to minimize the number of users we send to an inferior variant and to implement a variant with positive lift as quickly as possible? Don’t we all want to get rid of […] Read more…

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Bayesian AB Testing is Not Immune to Optional Stopping Issues

Fantasy vs real world in bayesian ab testing

Fantasy vs the Real World: Naive Bayesian AB Testing vs Proper Statistical Inference This post is addressed at a certain camp of proponents and practitioners of A/B testing based on Bayesian statistical methods, who claim that outcome-based optional stopping, often called data peeking or data-driven stopping, has no effect on the statistics and thus inferences […] Read more…

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