The Power at limits [🇷 for BE/BA]

posted by d_labes  – Berlin, Germany, 2009-10-07 13:32 (5682 d 07:18 ago) – Posting: # 4312
Views: 32,456

Dear All!

Back from the date with the Blonde downstairs an having some spare time ;-),

Seems ElMaestro's question is able to put the power to the limits.
Here results of power.equivalence.md around N=6:

R code:
library(MBESS)

alpha    <- 0.05
logscale <- TRUE
ltheta1  <- 0.8
ltheta2  <- 1/ltheta1
ldiff    <- 0.95
CV       <- 0.65                # added [HS]
sigma    <- sqrt(log(1+(CV)^2)) # added [HS]
n        <- c(4,6,8,10,12,14,16)
df       <- n-2
pow      <- mapply(power.equivalence.md,n=n,nu=df, MoreArgs =list(alpha, logscale, ltheta1, ltheta2, ldiff, sigma))
res      <- data.frame(n=n, power=pow)
res


Result:
   n        power
1  4 0.0045417784
2  6 0.0016203829
3  8 0.0009763342
4 10 0.0007993335
5 12 0.0007966979
6 14 0.0009067329
7 16 0.0011306148


I would expect power is increasing with increasing n.
Or miss I here something?

BTW: My SAS code shows the same effect.
All this is hairsplitting of course.


Edit: Added two lines above to allow copy-pasting of code to R-console. BTW, change the sample size vector to n<-c(4,6,8,10,12,14,16,38,40,152,154,344,346) and watch (the gamma-function needs the faculty, which runs out of steam - at least on 32-bit operating systems). [Helmut]

Regards,

Detlew

Complete thread:

UA Flag
Activity
 Admin contact
23,424 posts in 4,927 threads, 1,673 registered users;
92 visitors (0 registered, 92 guests [including 1 identified bots]).
Forum time: 20:50 CEST (Europe/Vienna)

There are two possible outcomes: if the result confirms the
hypothesis, then you’ve made a measurement. If the result is
contrary to the hypothesis, then you’ve made a discovery.    Enrico Fermi

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