You are here

This is a test website. For our live site please visit www.sagepub.com

Disable VAT on Taiwan

Unfortunately, as of 1 January 2020 SAGE Ltd is no longer able to support sales of electronically supplied services to Taiwan customers that are not Taiwan VAT registered. We apologise for any inconvenience. For more information or to place a print-only order, please contact uk.customerservices@sagepub.co.uk.

Logistic Regression
A Primer

Second Edition

Fred C. Pampel - University of Colorado - Boulder, USA

Volume: 132

Series:
Quantitative Applications in the Social Sciences

October 2020 | 152 pages | SAGE Publications, Inc

This volume helps readers understand the intuitive logic behind logistic regression through nontechnical language and simple examples. The Second Edition presents results from several statistical packages to help interpret the meaning of logistic regression coefficients, presents more detail on variations in logistic regression for multicategory outcomes, and describes some potential problems in interpreting logistic regression coefficients. A companion website includes the three data sets and Stata, SPSS, and R commands needed to reproduce all the tables and figures in the book. Finally, the Appendix reviews the meaning of logarithms, and helps readers understand the use of logarithms in logistic regression as well as in other types of models.

Available Formats

ISBN: 9781071816202	Paperback	Suggested Retail Price: $46.00	Bookstore Price: $36.80
ISBN: 9781071816189	Electronic Version	Suggested Retail Price: $38.00	Bookstore Price: $30.40

See what’s new to this edition by selecting the Features tab on this page. Should you need additional information or have questions regarding the HEOA information provided for this title, including what is new to this edition, please email sageheoa@sagepub.com. Please include your name, contact information, and the name of the title for which you would like more information. For information on the HEOA, please go to http://ed.gov/policy/highered/leg/hea08/index.html.

For assistance with your order: Please email us at textsales@sagepub.com or connect with your SAGE representative.

SAGE
2455 Teller Road
Thousand Oaks, CA 91320
www.sagepub.com

Series Editor’s Introduction

Preface

Acknowledgments

About the Author

Chapter 1: The Logic of Logistic Regression

Regression With a Binary Dependent Variable

Transforming Probabilities Into Logits

Linearizing the Nonlinear

Summary

Chapter 2: Interpreting Logistic Regression Coefficients

Logged Odds

Odds

Probabilities

Standardized Coefficients

Group and Model Comparisons of Logistic Regression Coefficients

Summary

Chapter 3: Estimation and Model Fit

Maximum Likelihood Estimation

Tests of Significance Using Log Likelihood Values

Model Goodness of Fit

Summary

Chapter 4: Probit Analysis

Another Way to Linearize the Nonlinear

The Probit Transformation

Interpretation

Maximum Likelihood Estimation

Summary

Chapter 5: Ordinal and Multinomial Logistic Regression

Ordinal Logistic Regression

Multinomial Logistic Regression

Summary

Notes

Appendix: Logarithms

The Logic of Logarithms

Properties of Logarithms

Natural Logarithms

Summary

References

Index

Supplements

Student Study Site

Sample Materials & Chapters

Chapter 1: The Logic of Logistic Regression

Chapter 2: Interpreting Logistic Regression Coefficients

Sage College Publishing

You can purchase or sample this product on our Sage College Publishing site:

Go To College Site

Related Products

This title is also available on SAGE Research Methods, the ultimate digital methods library. If your library doesn’t have access, ask your librarian to start a trial.

Find out more