Applied Logistic Regression Analysis

by Scott Menard

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. 

119 pages, Kindle Edition

First published June 29, 1995

Reviews

[Nmoversae Company · Rating 5 out of 5]

I enjoyed reading this book
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[J. Scott Frampton · Rating 3 out of 5]

This is a good book. It provides a clear understanding of logistic regression analysis. I use it as a textbook for a number of my statistics courses.

[Steven Peterson · Rating 4 out of 5]

Logistic regression analysis is an analogue to multiple regression--with the dependent variable pitched at the dichotomous level (just two values). It is a pretty sturdy statistical technique, not demanding a lot of assumptions about the nature of dependent and independent variables. This book is not terribly accessible (I get headaches in some sections), but it is a very nice brief introduction to the subject.

[Walker*Management*Library · Rating 5 out of 5]

Recommended by Dawn Iacobucci for wannabe geeks.