Average Reviews:
(More customer reviews)As its title suggests, this book is an excellent guide to using logistic regression in data analysis. I purchased this book because I needed to do several logistic regression runs for my dissertation. It turned out to be an extremely useful book for two reasons. First, it presents logistic regression alongside more traditional ordinary least squares (OLS) models. Therefore, if you already have a good understanding of OLS models, this book is very easy to follow. Second, its discussion of logistic regression issues in the context of SPSS or SAS makes it very easy to follow along with your own data analysis as you move through the book. Since statistical packages are always improving, this does date the book a little. However, this is a very minor concern. I believe Dr. Menard is to be commended for including issues regarding popular software packages in this work.
When compared to SAS's documentation, this book's greatest advantage is explaining in english (rather than mathematical notation) the assumptions and limitations of SAS's (and SPSS'S) algorithms. Its chapter on logistic regression diagnostics is alone worth the price of the book. In short, if you need to use logistic regression analysis and you already understand OLS, you cannot go wrong with this book.
Click Here to see more reviews about: Applied Logistic Regression Analysis (Quantitative Applications in the Social Sciences) (v. 106)
The focus in this Second Edition is again on logistic regression models for individual level data, but aggregate or grouped data are also considered. The book includes detailed discussions of goodness of fit, indices of predictive efficiency, and standardized logistic regression coefficients, and examples using SAS and SPSS are included. More detailed consideration of grouped as opposed to case-wise data throughout the book Updated discussion of the properties and appropriate use of goodness of fit measures, R-square analogues, and indices of predictive efficiency Discussion of the misuse of odds ratios to represent risk ratios, and of over-dispersion and under-dispersion for grouped data Updated coverage of unordered and ordered polytomous logistic regression models.
Buy cheap Applied Logistic Regression Analysis (Quantitative Applications in the Social Sciences) (v. 106) now.
No comments:
Post a Comment