Aspects of the text that stand out as different from other texts include:
1. A detailed explanation of different error rates for multiple comparisons. More detail is present than is useful for a beginning student, but the exposition is excellent as a reference for those who need it.
2. An unusually well-informed (and practical) discussion of assumptions.
3. Discussion of SAS Type II errors. Common practice is not always the most sensible, and the author's advocacy of the Type II approach for many problems is compelling.
4. A good discussion of mixed model assumptions (restricted and unrestricted models). I have not seen a comparable exposition of this potentially confusing issue.
5. The use of Hasse diagrams for mixed models. I had not worked with Hasse diagrams before I used this text, but find them to be useful tools for analysis of complex designs.

My only quibble is that some items in chapter 13 could be introduced earlier....although probably not fully covered. In particular, RCBDs without interactions could appear (with appropriate caveats) along with factorial designs. I confess some ambivalence on this issue, noting that I only quarrel because I am starting to get rushed for time by chapter 13.

If you want a cookbook, go elsewhere. If you want a highly mathematical approach, this is also not for you. For a serious treatment of real statistical issues, however, both analysis and design, I doubt if you can do much better.