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Applied Logistic Regression Analysis
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Applied Logistic Regression Analysis

Second Edition
  • Scott Menard - Sam Houston State University, USA, University of Colorado, USA
Volume: 106
December 2001 | 128 pages | SAGE Publications, Inc
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The focus in this Second Edition is on logistic regression models for individual level (but aggregate or grouped) data. Multiple cases for each possible combination of values of the predictors are considered in detail and examples using SAS and SPSS included. New to this edition:

· More detailed consideration of grouped as opposed to casewise data throughout the book

· Updated discussion of the properties and appropriate use of goodness of fit measures, R2 analogues, and indices of predictive efficiency

· Discussion of the misuse of odds ratios to represent risk ratios, and of overdispersion and underdispersion for grouped data

· Updated coverage of unordered and ordered polytomous logistic regression models.

 
Series Editor's Introduction
 
Author's Introduction to the Second Edition
 
1. Linear Regression and Logistic Regression Model
 
2. Summary Statistics for Evaluating the Logistic Regression Model
 
3. Interpreting the Logistic Regression Coefficients
 
4. An Introduction to Logistic Regression Diagnosis
 
Ch 5. Polytomous Logistic Regression and Alternatives to Logistic Regression
 
6. Notes
 
Appendix A
 
References
 
Tables
 
Figures

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