On CI calculation, untransformed metrics [General Sta­tis­tics]

posted by ElMaestro  – Belgium?, 2019-11-29 03:40 (303 d 16:55 ago) – Posting: # 20893
Views: 2,196

Hi all,

I never did much work on untransformed metrics for BE calculation, but I am facing a situation where it is mandated by an authority, and what I need is the CI for the ratio (not per se the difference). I'd like to be well prepared.

A relevant publication, at least for sample size, is Hauschke et al. from 1999.

The ratio of two normal distributions is not itself a normal distribution. How is the calculation of the CI for the ratio actually done when the upper and lower limits are percentages of mu(R) ?

I think Hauschke's paper is silent on the matter, as is Chow & Liu.

Note also that powerTOST's nomenclature seems to differ a bit (?) from Hauschke's in that it uses theta1 and theta2 where Hauscke would use f1 and f2. In powerTOST theta1 defaults to 0.8 when the limit for the ratio is actually 0.8*mu(R), or so I am reading it. I may be quite wrong?!?

Anyhow, the important part of this post is how the CI for the ratio is actually derived.

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.

Complete thread:

Activity
 Admin contact
21,079 posts in 4,396 threads, 1,468 registered users;
online 5 (0 registered, 5 guests [including 2 identified bots]).
Forum time: Sunday 21:36 CEST (Europe/Vienna)

Politicians use statistics like drunkards use lampposts:
not for illumination, but for support.    attributed to Hans Kuhn

The Bioequivalence and Bioavailability Forum is hosted by
BEBAC Ing. Helmut Schütz
HTML5