Inter and Total Variability [Power / Sample Size]

posted by Helmut Homepage – Vienna, Austria, 2011-09-02 16:21 (5416 d 03:00 ago) – Posting: # 7328
Views: 16,370

Dear Benjamin!

❝ […] Would be great if someone could give me some more details on that.


For references see this post and Hauschke et al.1,2

The between-subject coefficient of variation \(CV_b\) is calculated from the between-subject variance \(\sigma_b^2\):
\begin{equation}
CV_b=\sqrt{e^{\sigma_b^2-1}}
\end{equation}

Since we don’t know the between-subject variance of the population, \(CV_b\) has to be estimated from the model’s \(MSE_b\) and \(MSE_w\):
\begin{equation}
CV_b\approx\sqrt{e^{(MSE_b-MSE_w)/2}-1}
\end{equation}

❝ Also I read that one only gets the total variance out from a parallel study. The reason for that is what? Is it just the fact that the intra subject variability always exists, but cannot be measured by this kind of design?


Exactly! The fact that you observed just one occasion, doesn’t mean that variability between occasions (in the same subjects – therefore ‘within’ or ‘intra’) does not exist.
  1. Hauschke D, Steinijans VW, Pigeot I. Bioequivalence Studies in Drug Development: Methods and Applications. New York: Wiley; 2007. p 88.
  2. A note for users of Phoenix/WinNonlin: The output of a 2×2 cross-over study erroneously gives \(CV_b\) based on (1)
    Edit: Removed from the output in Phoenix 7.0; now it is up to you to apply the correct formula in a ‘custom transformation’ from the variance(s). BTW, if the EMA’s ‘all fixed effects’ model is used, only the within-subject variance is available.

PS: THX for bringing the problems with the contact form and the registration to my attention!

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