## Inflation of the TIE with Xu’s ‘Method F’? [Two-Stage / GS Designs]

Dear all,

I’m confused. Xu et al. (doi:10.1002/pst.1721) claim that for a range of CV 10–30% and n1 12–? and design constraints (α0 0.05, α1 0.0248, α1 0.0364, maximum total sample size 42, stopping for futility in the first stage if the (1–2α1) CI is entirely outside 0.9492–1/0.9492) the maximum Type I Error (assessed at a true GMR 0.80) is 0.050. So far, so good. But:

library(Power2Stage) power.2stage.fC(method="C", alpha0=0.05, alpha=c(0.0248, 0.0364),                 CV=0.2, n1=12, GMR=0.95, theta0=0.8, max.n=42,                 fCrit="CI", fClower=0.9492, targetpower=0.8,                 pmethod="shifted", nsims=1e6) TSD with 2x2 crossover Method C: alpha0 = 0.05, alpha (s1/s2) = 0.0248 0.0364 Interim power monitoring step included Target power in power monitoring and sample size est. = 0.8 Power calculation via shifted central t approx. CV1 and GMR = 0.95 in sample size est. used Maximum sample size max.n = 42 Futility criterion 90% CI outside 0.9492 ... 1.053519 BE acceptance range = 0.8 ... 1.25 CV = 0.2; n(stage 1) = 12; GMR= 0.95 1e+06 sims at theta0 = 0.8 (p(BE)='alpha'). p(BE)    = 0.053425 p(BE) s1 = 0.032461 Studies in stage 2 = 32.75% Distribution of n(total) - mean (range) = 16.7 (12 ... 42) - percentiles  5% 50% 95%  12  12  34

What? Am I missing sumfink?

Dif-tor heh smusma 🖖
Helmut Schütz

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