Hi everyone!
Context: I have a process A which is my reference, and I developped a process B which I want to assess its comparability to process A. To do so, I plan to use a TOST (equivalence test) using the process A's 3xSTD (standard deviation) as a treshold. Now, I want to know how many time should I repeat process B to be sure to be able to detect such variation (knowing that a run is a significant amount of money).
Option 1: I wanted to use the Sample size & Power tool, with 2 sample means comparison, with an alpha of 0.1 (2x0.05 for each process), a STD = 1, no extra parameter, Difference to detect = 3 (3x STD of 1), Power = 0.95, & I obtain 7, so 4 runs of process B to compare to 4 runs of process A to ensure the comparability.
Option 2: To use the t-distribution (as shown below) and therefore suggest 6 runs:
What do you think about the two options, which one is best for this case? Do you have any other tool I didn't think of?
Thanks a lot !
@martindemel maybe ?
