What are the challenges of sequential testing in statistics?

What are the challenges of sequential testing in statistics?

Sequential testing involves analyzing data as it is collected, which can lead to challenges like increased complexity in design and interpretation.

Can you explain why increased complexity is a challenge?

Increased complexity arises because sequential tests require careful planning to avoid biases and ensure valid conclusions, making them harder to implement.

What are some common biases in sequential testing?

Common biases include the peeking bias, where researchers may look at results too early, and the stopping rule bias, which can affect the validity of the test.

How can these biases be mitigated?

Mitigating these biases can involve pre-registering the study design, using strict stopping rules, and employing statistical methods that account for sequential analysis.

Are there specific fields where sequential testing is more challenging?

Yes, fields like clinical trials and adaptive learning environments often face unique challenges due to ethical considerations and dynamic data.