Multiple comparison corrections

Experimentation results are now more statistically rigorous. LaunchDarkly automatically applies multiple comparison corrections when analyzing experiments with many metrics or variations. This reduces false positives and ensures your reported wins are reliable even in complex tests. Now teams can move faster with confidence, knowing their decisions are backed by best-practice statistical methods.

Get started with multiple comparison corrections in our guide.