I would suggest that you reread those chapters mentioned earlier as you haven't extracted the proper elements for a power analysis. You simply can't use the observed data to do a power analysis on the observed effects -- this is a retrospective power analysis and there are many paper showing that this is nonsense. Visit SFU Statistics - Power computations in complex experiments for some SAS examples, e.g. the power analysis of the split-plot design. What you need to do, once you have generated the random data with the corresponding means and std from each combination of center and treatment, is estimate the two variance components. Your experiment is an example of a Generalized RCB design. Centers are blocks, each treatment occurs in all centers, and you have multiple replicates of each treatment in each centre (unlike a classic RCB where there is one replicate of each treatment in each block). There are several papers describing the analysis of a GRCB -- try Addelman, S. (1969). The Generalized Randomized Block Design. American Statistician, 23, 35-36. http://dx.doi.org/10.2307/2681737 . YOur model is missing one variance component representing the centre*treatment interaction, and needs to be refit. Proc Mixed on the simulated data, with an appropriate model, should give you these. THen you use the variance components and proposed sample sizes to estimate the power etc as shown in Stroup's original paper or the SAS for Mixed Models book. Carl Schwarz
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