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

posted by Helmut Homepage – Vienna, Austria, 2016-12-25 02:49 (2651 d 11:14 ago) – Posting: # 16876
Views: 3,674

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?

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