Customer Reviews

Designing Experiments and Analyzing Data: A Model Comparison Perspective, Second Edition

5 star:		(5)
4 star:		(0)
3 star:		(3)
2 star:		(1)
1 star:		(0)

 

 

I continue to select this text for a graduate course in advanced experimental design. The book is not easy, and that is one reason why I like it. It presents a thoughtful scholarship on controversial issues pertaining to the use of inferential statistics as a tool to assist the researcher in making decisions about the validity and strength of functional relationships present in the data. The book eliminates the naive overconfidence that sometimes results from cookbook applications of algorithms to the results of experiments. It shows that the process of discovery and data analysis is never complete and that the general linear model is an imperfect technique by which to discern orderliness in nature where intersubject variability is a given.

This is a practitioner's book, not a scolar's. I'm not a scolar -- never have been and never will be. I love this book. It's lucid, it's sensible and it's great statistics. It goes thoroughly into the logic of linear model ANOVAs yet the bulk of the exposition is in the simple English language -- it has no calculus and no eigenvectors and almost no matrix algebra. You need an acquaintance with elementary one-way ANOVA but no more background than that. The authors pace it carefully and are not afraid of a bit of repetition for the sake of clarity (something I always appreciate when I'm reading new technical material). It's one of the best $105 dollars I've ever spent. I got loads out of it all the way through and it's a big book. The explanation of multivariate repeated measures is worth the price alone.

Maxwell & Delaney have created one of the best textbooks for introducing the reader to advanced topics in statistics. The book gives extensive coverage in both theory and application of ANOVA, Post-hoc comparisons, ANCOVA, Factorial Design, and Multilevel Modeling. I would highly recommend this text for a graduate statistics course. I continue to use this book as a reference in my analyses and writing. While many will find this text to be heavy (and it is), it is because of the comprehensive coverage of topics. Like most statistics books, re-reading this book offers further insight and understanding.

The authors provide a detailed analysis about the nuances of statistics but the writing style is very dry. Also, there are few succinct summaries, making it difficult to look up specific concepts or formulae quickly.

Maxwell and Delaney are the Sigfreid and Roy of the statistical world. Their examples are like elaborate shows meant to tantalize the senses. I only wish I could give it more than 5 stars.

This edition is similar to the previous one. It is without peer in terms of scholarship. It is also not easy to read and digest, and that's the way it should be for a serious treatment of research methods. After all, the applications of such methods and the interpretation of results can profoundly affect our lives.

Without any doubt, this is a comprehensive book in this field. However, because the authors tried to demonstrate their superior english writting abilities, they made the whole text hard to understand for students. From my point of view, as a new professor, I don't believe that recommending this book is appropriate.

The book is extremely confusing. Some terms are worded differently from any other stats text I had used in the past. I am assuming this is written for a super advanced stats class. However, most excersises in the book can be done in a much easier way, using different formula formats, etc. Verdict: there are other stats text that contain the same information but are easier to comprehend by grad. students.

It is not very useful book! Too bulky , too much explanations, does not have SAS codes ....