Fieller’s (‘fiducial’) confidence interval [General Sta­tis­tics]

posted by ElMaestro  – Belgium?, 2019-11-30 05:11 (302 d 14:37 ago) – Posting: # 20899
Views: 1,649

Dear d_labes,

you left me baffled.

» » For such cases we are setting logscale to False, right?
»
» Correct in so far if we use the approximation that the estimate of µR is (statistically) greater than zero. A very reasonable assumption for the usual metrics AUC and Cmax IMHO.

Please explain then what exactly it is that power.TOST calculates when I use logscale=F.
Does it calculate power for a hypothesis based on a difference or for a ratio?
Which difference? Which ratio?

» But this has than nothing to do with Fieller’s (‘fiducial’) confidence interval, a more correct method for deriving a confidence interval for the ratio of untransformed PK metrics.

The mention of Fieller was not mine. I am quite confused now, what it is power.TOST tries to calculate when I do logscale=F.

I am convinced the assuming theta1=-0.2 by default when logscale=F is a misnomer. theta1 is elsewhere understood as an equivalence margin expressed as a ratio and that can't realistically be negative. If powerTOST tries to emulate Hauschke's paper then -.2 is f1, not a theta.
We need to be careful here about f, delta and theta.

I could be wrong, but...

Best regards,
ElMaestro

R's base package has 274 reserved words and operators, along with 1761 functions. I can use 18 of them (about 14 of them properly). I believe this makes me the Donald Trump of programming.

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