## ABEL is a framework (decision scheme) [Power / Sample Size]

Thank you for the explanation, it seems I havent taken the distribution of CV into account (jumping over and below the limit CV=30%).

❝ Therefore, simulations are needed. At a true CVwR = 30% we have – roughly* – a 50% chance that in the actual study CVwR > 30%. Then we could expand the limits, gain power for a given sample size, or need less subjects for a certain power than we would need in ABE.

❝ […] Now the sample sizes are identical. Power for ABEL is slightly larger than for ABE because there is a certain – while small – chance to expand the limits.

So the sample size with ABEL is always smaller or equal to ABE right (with the same arguments)? Similarly, power for the same number of subjects is always higher (or equal) with ABEL than with ABE (as shown in my reformulated question at the end of the first post or in your example with n=21 for ABE vs. ABEL)?

1. So in case regulators (EMA region) ask us to calculate post hoc power (regardless of how irrelevant it is) of a study with 2x3x3 design with CVwr=25%, we should calculate it with power.TOST for AUC and for Cmax when we didnt mention anything about widened limits (ABEL) in the protocol (hypothetical scenario)? And on the other hand, for Cmax we should calculate it with power.scABEL when we mentioned widened limits (ABEL) in the protocol?

2. Another hypothetical scenario: If we get information from the literature about a drug's CVw (Cmax) of around 30% (lets say a range of 25-35%) and if we get a drug's CVw of 22% from our pilot study, can we then do a regular study with design 2x3x3 (in case we get CVw for Cmax 35% so then we could widen the limits and use ABEL)? And if then our drug's CVw from this regular study is lets say 21%, can agencies ask us to justify replicate 2x3x3 design as if why didnt we use conventional 2x2x2 design if we got CVw=22% in our pilot study?

BEQool