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Rating: 
Summary: For the Statistically Savvy Only
Review: As a student, I have taken the opportunity to read many texts on research methodology. This book is one of the best. I appreciated the balance between technical information and readability. The book offers the reader the ability to gain in depth knowledge about regression analysis and linear models, yet presents the information in an understandable way. Other texts have proven too simplistic to answer important questions or too complex to understand. This book is a nice balance of both features.
Rating: 
Summary: An insightful, understandable, and practical guide to MRC
Review: As a student, I have taken the opportunity to read many texts on research methodology. This book is one of the best. I appreciated the balance between technical information and readability. The book offers the reader the ability to gain in depth knowledge about regression analysis and linear models, yet presents the information in an understandable way. Other texts have proven too simplistic to answer important questions or too complex to understand. This book is a nice balance of both features.
Rating: 
Summary: Get it now!!! Best on the subject.
Review: Dr. Fox makes an excellent contribution to the student community across geographies. The text is an excellent balance between theory and practical applications of the linear regression methodology. The author is extremely clear in explaining not only simple and multiple linear regression, but also topics such as bootstraping, logistic and other regression techniques for non normal response variables. The book do not fall down near your toes: the topics are covered in a depth that is amenable for a PhD student.
It is very interesting also to look at the many side comments and suggested readings that the author introduces many times in the book. I congratulate Dr. Fox for this clear, understandable and easy to follow text.
Rating:
Summary: For the Statistically Savvy Only
Review: I am now using this textbook for a graduate statistics course. I personally do not find it to be the most accessible book for those who are not already highly schooled in statistics, linear algebra, and calculus. There is an attempt at the back of the book to introduce you to the only linear algebra and calculus you "need" to understand the book. But I think the book continues to go far beyond what is accessible to someone being introduced to this information for the first time. I think the book is probably excellent if you are already familiar with regression, calculus, and linear algebra. However, for those who are not, I would recommend Paul Allison's "Multiple Regression: A Primer" to get OLS and Pampel's "Logistic Regression: A Primer" to get Logistic. These books introduce you to the same concepts but without all the extra stuff that most people won't use anyway.
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