Sequential Testing vs Fixed-Horizon Tests: When to Use Each

Sequential testing vs fixed-horizon tests: when to use each

Imagine you're in the middle of a critical product launch. You've set up an experiment to see what works and what doesn't. But how do you decide when to stop and analyze the results? This is where the choice between sequential testing and fixed-horizon tests comes into play. Each has its own perks, and knowing when to use which can give you a real edge.

Let's dive into these two approaches and figure out how they can fit into your testing strategy. Whether you're aiming for fast insights or solid long-term data, understanding these methods can help you make smarter decisions.

Setting the stage for structured evaluation

Before diving into data, having a clear plan is essential. Sequential testing is like placing a series of well-informed bets. It allows you to check in on your data without increasing the risk of false positives. Curious about how this works? Check out our detailed post on sequential testing.

Start with a solid hypothesis and a primary metric. Define your stop rules and set clear boundaries. By scheduling interim checks, you can ensure your results stay reliable. For example, using mSPRT helps maintain accuracy.

Keep your data clean and trustworthy. Remove flaky results by isolating problematic tests. Martin Fowler has great insights on dealing with non-determinism: eradicate non-determinism.

Here's a handy checklist to guide you:

• Define your hypothesis and key metrics

• Set stop boundaries and schedule peeks

• Ensure data hygiene and account for seasonality

Choosing the right approach is like picking the right tool for the job. Fixed-horizon tests are great for subtle effects over longer periods. For broader context, check out this testing guide.

The mechanics of sequential testing

Sequential testing lets you keep an eye on key metrics throughout your experiment. This means you can react quickly if something unexpected pops up. It's perfect for situations that demand fast decisions.

To prevent inflated false positives, sequential testing uses adjusted boundaries. Every time you review your data, the criteria for significance are updated. This means you get earlier signals on meaningful changes without jumping to conclusions.

Here's how it works:

• Continuous monitoring: Stay updated as data comes in

• Dynamic thresholds: Adjust goals with each check

For a deeper dive, explore sequential testing on Statsig or Martin Fowler’s guide. You can also check out the Statsig documentation for practical setup tips.

The logic of fixed-horizon tests

Fixed-horizon tests start with a set sample size and duration. You decide these before collecting any data, removing the temptation to peek too soon.

This approach minimizes mid-trial bias by ensuring decisions are only made at the planned end. This way, any observed effects are genuine, not just flukes from early stopping.

Key points include:

• No need for adjustments during the test

• One clear decision point at the end

• Simpler setup compared to sequential testing

While it lacks flexibility, this method offers transparency. You know exactly how and when results will be assessed. For more insights, see martinfowler.com/testing.

Finding the right fit

Deciding between sequential testing and fixed-horizon methods depends on your goals. If you need quick feedback and the ability to pivot, sequential testing is your go-to. It helps catch issues early, allowing for rapid adjustments.

For decisions requiring stable, long-term data, fixed-horizon tests are ideal. They offer a complete dataset, minimizing noise and supporting confident decisions.

Consider these questions:

• Do I need immediate problem detection?

• Am I focusing on long-term accuracy or short-term agility?

Sequential testing is great for agile teams that value speed, and Statsig has more resources to help you implement these strategies effectively. For more detailed insights, explore Martin Fowler’s articles.

Closing thoughts

Choosing the right testing method is key to effective decision-making. Whether you need the agility of sequential testing or the reliability of fixed-horizon tests, understanding these approaches will help you navigate your experiments with confidence. For further reading, check out our resources on Statsig.

Hope you find this useful!