Description

Book Synopsis

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.




Table of Contents
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

Applied Logistic Regression Analysis

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    £999.99

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    A Paperback by Scott Menard

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      View other formats and editions of Applied Logistic Regression Analysis by Scott Menard

      Publisher: SAGE Publications, Inc
      Publication Date: 12/5/2001 12:00:00 AM
      ISBN13: 9780761922087, 978-0761922087
      ISBN10: 0761922083

      Description

      Book Synopsis

      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.




      Table of Contents
      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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