[R-sig-ME] power calculations in mixed models

[Mark Kimpel]

I have data from a micro-array experiment that has turned out to be
underpowered. Classical power calculations based on observed variance
of presumably non-differentially expressed genes and the delta that we
would like to measure have led to this conclusion. We have enough of
each sample to re-run the assays, thus obtaining technical replication
within sample, which would be a random-effect. As a simplistic
approach to predicting the power obtained when using technical
replication, I have performed a simulation using averages for each
sample. This demonstrates that variance is cut in half with
replication.

I assume that power would be further increased in a real experiment if
all measurements are included in a mixed-effects model. Is that likely
to be true? If it is, is there any way to predict, based on the
knowledge we already have, the power of the data-set expanded with
technical replication?

Thanks,
Mark

-- 
Mark W. Kimpel MD ** Neuroinformatics ** Dept. of Psychiatry
Indiana University School of Medicine

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