Comparing to zero

[Litvak Vladimir]

> My first reaction is: if A is different from B, then (A-B) is different from
> zero, and hence (A-B)/B is also different from zero (given that B is not
> zero). So what is the use of testing A==B separately from testing whether
> (A-B)==0? Do you expect your statistical sensitivity to be larger?

The point is I do the normalization for each subject separately. So I get
% change for each subject and not absolute values that can be very
different between individuals. I didn't think it violates any of the
assumptions of clusterrandanalysis but if it does I'll probably have to
look for other ways.

>
> In clusterrandanalysis, the clusters are grown using a thresholded parametric
> statistical representation of the effect of interest. The summed parametric
> statistical measure over the whole cluster is subjected to the randomization
> procedure (testing the hypothesis of exchangeability), which results in a
> non-parametric test. I am not aware of a parametric statistical measure for
> which it would be possible to define a meaningfull threshold for the
> clustering based on the ratio (A-B)/B. It could be done however using a
> randomization test that is not based on clusters.


I don't understand why this normalized data is different from raw data.
You can define the distribution under the null hypothesis using
permutations and proceed from there. If there is something basic I don't
understand please explain it to me because it's important to know the
limitations of the method.

Thanks,

Vladimir