Interim analyses and stopping rules — does this still hold? posts 31–35

A treatment-policy estimand asks what happens to people assigned to a strategy, including those who abandon it. A hypothetical estimand asks what would have happened had everyone continued. Both are legitimate and they give different numbers.

It is worth stating the boring hypothesis before the interesting one.

Absolute and relative effects answer different questions. Write down the event rate in each arm and the difference between them; everything quotable is derived from those two numbers.

Somebody will have a better source than mine, and I hope they post it.

Post #31 describes the usual case. This is about the unusual one.

I would be cautious about generalising from the Interim analyses and stopping rules example above. It is a good example. It is one example.

Adding the measurement that post #31 says would settle it.

Practical experience of Interim analyses and stopping rules, offered as one case with the conditions stated, not as a general finding. Conditions first, because they are what make it interpretable.

Absolute numbers, not just relative: a 30% relative reduction tells you the ratio but not the practical magnitude. The event rate in each arm and the difference between them tells you how many people benefit.