Bioequivalence and Bioavailability Forum

Dear all,

I stumbled across an interesting issue. Let’s say we plan for a replicate pilot study (RTR|TRT) in order to design the pivotal in the same design. I want to use the upper CL of the estimated CV (40%) by CVCL(CV=0.4, df=2*n-3, side="upper").

pilot n  CLupper
   16    0.525
   20    0.506
   24    0.494
   36    0.472

Sure. Now let’s plan the pivotal (T/R 90%, 80% power) for EMA’s method by sampleN.scABEL(theta0=0.9, CV=CV, design="2x2x3").

  CV   pivotal n  power   total n
0.525      44     0.8154    60
0.506      42     0.8021    62
0.494      42     0.8046    66
0.472      42     0.8046    78

In some cases we are already crossing the 50% cap. The larger pilot size does not pay off.
Let’s play the game for a CV of 30% (only 50% chance of scaling). If you prefer one-liners, use: sampleN.scABEL(theta0=0.9, CV=as.numeric(CVCL(CV=0.3, df=2*n-3, side="upper")[2]), design="2x2x3"). I got:

pilot n  pivotal n  power   total n
   16        46     0.8008    62
   20        48     0.8058    68
   24        48     0.8007    72
   36        50     0.8046    86

Amazing. Small is beautiful?