Hi, I'm not sure i agree with the idea that a test can be too powerful. This is a common argument in simulation experiments, that because you can do an infinite number of replicate simulations, somehow the differences detected are not real. In fact, the differences are real. They may not be biologically (or geologically or whatever field you are in) significant, but they are still real. That is why it is better to decide first on the magnitude of difference that you consider significant. Now, in the case of deviation from normality, I suppose you wouldn't have much intuition about what is significant, but the relevant question is what is the effect of small deviations from normality on your test or conclusions of your analysis? These kinds of studies are out there in the statistical literature for many tests (T-tests etc.) --I'm not sure how much has been done to look at the robustness of geostatistical analyses, but there are probably some studies (does anyone know?) I would not opt for a less-powerful test just to justify an assumption - that's, like, unethical or something.
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