Fieller’s (‘fiducial’) confidence interval [General Statistics]
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!
- On CI calculation, untransformed metrics ElMaestro 2019-11-29 03:40 [General Statistics]
- Fieller’s (‘fiducial’) confidence interval Helmut 2019-11-29 10:03
- On CI calculation, untransformed metrics PharmCat 2019-11-29 12:05