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Rating: 
Summary: Can't beat it
Review: ...This book is the source of all you need. It's hard going at times, but so's the subject. The book's 15 years old and remains the best guide to the analysis of correlated data. It's a reference book, one I value as much as a good dictionary. To use it as a text would be misguided unless the instruction was aimed at a sophisticated audience.
Rating: 
Summary: MRC Analysis---good book overall
Review: Cohen and Cohen's MRC analysis book is well versed and easy to understand for someone that is familiar with MRC terminology, however, for first year graduate students, the text is very equivocal. The book is lacking ample illustrations of complex problems, leaving students to rely on outside sources. Also, the book uses unfamiliar symbols that do not correspond with other MRC books, which intensifies the confusion level of the students even more.Overall, the text is a great addition to a statistical library, and this reviewer recommends it, in spite of being a sub-par book for first year graduate students.
Rating:
Summary: Can't beat it
Review: I agree with the previous reviewer that there are times when the exposition in the book gets a bit intense; but c'mon! We're dealing with statistics. You gotta sweat a bit. That's when learning happens. In my opinion the book is extremely clearly written. And although you may have to re-read a few sentences a few times, the basic tools for understanding most every major aspect of MRC is embedded in the text. In sum, this was a great book that I read as a 2nd-year graduate student in psychology. Unlike the first reviewer, I turned to this text when I got confused during the course lectures!
Rating:
Summary: Best MRC Book Ever
Review: I agree with the previous reviewer that there are times when the exposition in the book gets a bit intense; but c'mon! We're dealing with statistics. You gotta sweat a bit. That's when learning happens. In my opinion the book is extremely clearly written. And although you may have to re-read a few sentences a few times, the basic tools for understanding most every major aspect of MRC is embedded in the text. In sum, this was a great book that I read as a 2nd-year graduate student in psychology. Unlike the first reviewer, I turned to this text when I got confused during the course lectures!
Rating: 
Summary: Issues of Applied Multiple Regression
Review: The Applied Multiple Regression (LRM) model has been in use in statistical analyses for many years; but it was not until the late 1960's that a model was used to provide a multivariate analysis of the Katsulares/Mitri heart study data that its full power and applicability were totally appreciated. Since then the LRM model has become the standard method for regression analysis of dichotomous data in many fields, especially in the health sciences. This new and updated edition of the classic bestseller provides a focused introduction to the LRM model and its use in methods for modeling the relationship between a dichotomous outcome variable and a set of covariables.
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