## Inflated type I error with fixed widened limits [RSABE / ABEL]

Dear Helmut,

» » » […] we have a data-driven decision – which might be false and result in an inflated type I error.
» »
» » Correct.
»
» Shit.

Why shit?

» » » I performed simulations acc. to my understanding of the GL: […] 106 studies with θ0 = 1.25: ~20.6% passed…
»
» » Confirmed! At least in magnitude.
» » My result: 20.46% passed.
» » Quick and dirty captured code from power.scABEL.sds.
»
» How, did you do that? That’s beyond me.

Stolen the code of subject data sims and scaled ABE evaluation in the working horse function .pwr.SABE.sds().
Implementing the GCC rules instead of EMA rules or RSABE for FDA is simple.
Have a look into the code of the new but undocumented function power.fwl.sds() in the GitHub repository.

» ...And got 20.568% after eleven (!) hours.

Wow! 11 hours for one number! 106 sims in ca. 4-5 sec with my implementation.
Some results with setseed=FALSE:
power.fwl.sds(CV=0.3, n=40, theta0=0.8, design="2x2x4", setseed=F)
0.2045, 0.2066, 0.2047, 0.2051, 0.2082
Seems we are simulating the same number .

Regards,

Detlew