Reviews for Linear Mixed Models: A Practical Guide Using Statistical Software

The average rating for Linear Mixed Models: A Practical Guide Using Statistical Software based on 2 reviews is 4.5 stars.

Review # 1 was written on 2010-05-30 00:00:00 Laura Rebbe This is a reference book in the optimization field. The proofs may not be the most formal but they are clearly and well written. What I especially like in this book is the buildup for every concept and proof. It always starts with the general statement of a problem then a few examples that re-iterate some ideas used to solve each of the cases. Then it moves onto proving the solution for the general problem at which point you already have a sense of where this is going. I've rarely seen chapters put together so cleanly. For example, for the proof of KKT (a fundamental theorem) the authors take you through LICQ, the relationship between the tangent cone at a feasible point and the set of linearized feasible directions, the Farcas Lemma then the KKT proof. I appreciate they prove something that's so fundamental. The book has an appendix with some of the necessary math that's outside of this book's scope, something I found useful as it makes it self contained.

Review # 2 was written on 2013-03-13 00:00:00 Andy Mackie Dense, timeless and comprehensive. The density and mathematical nature of the material means every page takes much longer to consume than you expect - a slow read, but fully capable of taking a post-calculus computer science student to being a fully competent optimizer.