An Introduction to Applied Multivariate Analysis with R (Use R!)

I found the first 7 chapters (typical MVA) pretty useful: Easy to understand and provides with enough underlying mathematics. Chapter 8 on repeated measures is a disappointment: It contains quite a few errors that, I believe, the authors are unknown. Take the "timber" example on pp 235. First, the method= should be "REML" for both timber.lme and timber.lme1. The reason is because a LRT is conducted on pp 237. For comparison of models with the same mean structure ("fixed part") but with different "random" parts, REML is required. Second, the p-value for the LRT is 1, which is VERY LARGE instead of "very small" as stated in the text. Furthermore, the p-value for the LRT by anova() is incorrect! The actual p-value should be calculated from a mixture of 2 chi-squared distributions.

The content is great, what is not good are the printed versions, it looks like photocopies. I bought Springer and it's the first time I received photocopies instead of a real printed book. I don't know if is a fake edition from book182wire or Springer delivered on that way.

Indeed, introduction of multivariate measures is INTUITIVE with graphs and formulas added. Although English is foreign language to me, this book is very intuitive, not easy, to read it! And this book has CRITICAL views on multivariate measures, so it is FAST to understand them! the number of stars is 7.

This book is an outstanding introduction to multivariate statistics. Everitt and Hothorn explain things very clearly, with examples that you can follow along with in R. They give commands and output so that it all makes sense even if you're not following along. They don't make too many assumptions about your level of math or R. I would say this is perfect for a graduate student or similar level intent on teaching themselves some statistics.

Great instructional book

Very, very dense read. There is an over reliance on jargon in each chapter to the point it becomes almost indecipherable.

The treatment of most topics is very superficial. It is understandable that the authors may have wanted to keep the book to a manageable length and choose to describe only a few methods in each class. However, even those few methods are described poorly. Neither the theoretical basis nor the mathematical formulation is sufficient for understanding the methods. Finally, the code is also neither well commented nor well described.The book came across as a poorly put together assortment of concepts, mathematics, and R code which are disorganized and at least to me, proved useless.

I am a beginner of R.R is such a powerful language and also a handy tool.This book is just what I need.Love it.

I am a non-statistician and have bought and used many stats books, but would rate this as my favourite. Very well written, and covers more than other introductory books that I own and use. I highly recommend it, very practical, with excellent examples. Hope for a new edition soon covering some of the new packages such as lme4.

If you need a practical explanation on how perform multivariate statistics and understand them this is your book.

It is a concise and well-structured book. Good to get started!

Nice introduction to multivariate analysis in R.

I cited this a few times in at least 2 reports. Concise, straightforward and I like how it's written.