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- How is minimum detectable effect calculated?
- How do you read a minimum detectable effect size?
- How does MDE affect sample size?
- What is MDE in AB testing?
How is minimum detectable effect calculated?
So, you have to configure an experiment in such a way that it declares the winner when the conversion rate difference is at least 22% – 20% = 2%. To set that up, you have to count your estimated MDE. In this example, 2% of the 20% baseline conversion rate is 10% – this is your estimated MDE for the experiment.
How do you read a minimum detectable effect size?
The minimum detectable effect size is the effect size below which we cannot precisely distinguish the effect from zero, even if it exists. If a researcher sets MDES to 10%, for example, he/she may not be able to distinguish a 7% increase in income from a null effect.
How does MDE affect sample size?
The larger the MDE, the smaller the sample size needed to run your experiment. And vice versa. The smaller the MDE, the bigger the sample required for your experiment to be adequately powered.
What is MDE in AB testing?
The MDE is the minimum effect size that should be detected with a certain probability. In literature, the term Minimum reliably Detectable Effect has been suggested as a more appropriate term, which fits better to the definition above. To be clear, the MDE is not the effect size we expect or want.
