CI for Transformed data Unbalanced study [General Sta­tis­tics]

posted by Helmut Homepage – Vienna, Austria, 2007-03-07 13:04 (6680 d 10:37 ago) – Posting: # 565
Views: 32,039

Dear USFDA_EMEA!

❝ ❝ Let's call Xt the LSM of the test, and Xr the LSM of the reference (log-scale).


❝ Can you help me with the formula for LSM (I wish to do a manual calculation, for verification purposes) and a brief explaination about why this method is used for unbalanced study?


The calculation is not different from a balanced study.

I’ll give you an example for the reference:
Calculate the (arithmetic) mean of log-transformed values in sequence 1 (if seq 1 = RT from period 1) as
Xr1 = sum ( Xr1 … n1 ) / n1

Calculate the (arithmetic) mean of log-transformed values in sequence 2 (if seq 2 = TR from period 2) as
Xr2 = sum ( Xr1 … n2 ) / n2

LSM for the reference is the arithmetic mean of Xr1 and Xr2
Xr = ( Xr1 + Xr2 ) / 2 )


The difference Xt – Xr is also called MLE (the Maximum Likelihood Estimator) of the true difference Mu(t) – Mu(r), which is slightly biased according to the degree of ‘unbalancedness’.
A better estimate of the true difference is MVUE (the Minimum Variance Unbiased Estimator), however, its calculation is a little bit tricky (involves the Γ-distribution).
For details see Chow & Liu’s book.

Dif-tor heh smusma 🖖🏼 Довге життя Україна! [image]
Helmut Schütz
[image]

The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes

Complete thread:

UA Flag
Activity
 Admin contact
23,424 posts in 4,927 threads, 1,674 registered users;
29 visitors (0 registered, 29 guests [including 9 identified bots]).
Forum time: 00:41 CEST (Europe/Vienna)

Complex, statistically improbable things are by their nature
more difficult to explain than
simple, statistically probable things.    Richard Dawkins

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