Deficiency letters [Two-Stage / GS Designs]

posted by Helmut Homepage – Vienna, Austria, 2013-12-04 15:50 (4219 d 07:27 ago) – Posting: # 12000
Views: 25,443

Hi Kumar,

❝ […] if I want to demonstrate that type error inflation did not impact on my study then can I demonstrate this by simply showing 90% CI as well as 94.12% CI for GMR of PK parameters within the acceptance limits (80% to 125%).


This was actually the response to deficiency #1. However, post hoc switch of statistical methods (from Method C to B) is really bad practice, but the regulator insisted on it. :-(
If you expect problems (only in Europe!) plan the study already for Method B.

❝ also I am not getting how to interpret Response 2


The study’s CV was 30.65% observed in 49 subjects. Potvin’s closest table entry is for CV 30% and n1 48 (αemp 0.0494). I simulated αemp with the study’s values and got 0.0494 as well (106 simulated studies). It’s easy to calculate the confidence interval based on the binomial test. In R:

sims  <- 1e6     # number of simulated studies
alpha <- 0.0494  # empiric risk type I
binom.test(alpha*sims, sims, alternative="two.sided", conf.level=0.95)

getting:

        Exact binomial test

data:  alpha * sims and sims
number of successes = 49400, number of trials = 1e+06, p-value < 2.2e-16
alternative hypothesis: true probability of success is not equal to 0.5
95 percent confidence interval:
 0.04897608 0.04982653
sample estimates:
probability of success
                0.0494


If you run a study with Method B and still get such a weird deficiency letter – and don’t have the means to run simulations – it should be possible to look at the 95% CI. IMHO Bonferroni’s α 0.025 should keep the overall risk type I <0.05 for any two-stage method. Ask a statistician.

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