Great post! [Outliers]

posted by Helmut Homepage – Vienna, Austria, 2019-02-07 10:37 (827 d 00:40 ago) – Posting: # 19887
Views: 4,615

Hi Zizou,

at a first look your arguments are convincing indeed.

A basic assumption in BE is that what we observe in the study is an unbiased sample of the population, i.e., the true (but unknown) distributions of the sample and the population are identical. Only then we can extrapolate the study’s result to the patient population (BE as a substitute for therapeutic equivalence). As stated in HC’s guidance parametric methods are not robust against extreme values. My example:

 n  method          PE       90% CI     CVintra  CVinter
12  LME           110.15% 77.60–156.36%  50.1%    NA   
(negative variance component)
12  ANOVA         110.15% 77.60–156.36%  50.1%    NA
11  LME            92.45% 78.34–109.11%  21.3%   22.2%
12  nonparametric  98.95% 76.24–130.06%   NA      NA   
(note: 91.78% CI)


Observations:Time allowing (ha-ha) I will try some sim’s where I replace one value with the true x±6σ. Asymptotics are generally fine if n≥30. Hence your suggestion for CV 30% makes sense (GMR 0.95, power 80% → n 40). But I will also try one with a lower CV of 15% (n 12).



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