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

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.

Pass or fail!
ElMaestro