Relevant: The PK metric with highest CV [Power / Sample Size]

» You could use function power.2TOST() of the R-package PowerTOST to explore various correlations (ρ). This issue is a little bit academic because ρ is rarely known.
»
»
• An early truncated partial AUC can be highly variable as well.

Hi Helmut,

Thank you for the reply. I am afraid that I did not state clearly. I still want to clarify do you mean that for the estimation of sample size, the power need to be calculated as:
Overall power = (power of AUC0 * power of AUCinf * power of Cmax)
like 0.8=（0.92*0.92*0.92）
And it could not be simplified as Overall power = (power of AUC0 * power of Cmax) to decrease power needed of each for the lack of ρ?

Thanks again.