The Chicago Guide to Writing about Multivariate Analysis, Second Edition
by Jane E. Miller
University of Chicago Press, 2013
Cloth: 978-0-226-52786-4 | Paper: 978-0-226-52787-1 | Electronic: 978-0-226-03819-3
DOI: 10.7208/chicago/9780226038193.001.0001
ABOUT THIS BOOKAUTHOR BIOGRAPHYREVIEWSTABLE OF CONTENTS

ABOUT THIS BOOK

Many different people, from social scientists to government agencies to business professionals, depend on the results of multivariate models to inform their decisions.  Researchers use these advanced statistical techniques to analyze relationships among multiple variables, such as how exercise and weight relate to the risk of heart disease, or how unemployment and interest rates affect economic growth. Yet, despite the widespread need to plainly and effectively explain the results of multivariate analyses to varied audiences, few are properly taught this critical skill.

The Chicago Guide to Writing about Multivariate Analysis
is the book researchers turn to when looking for guidance on how to clearly present statistical results and break through the jargon that often clouds writing about applications of statistical analysis. This new edition features even more topics and real-world examples, making it the must-have resource for anyone who needs to communicate complex research results.

For this second edition, Jane E. Miller includes four new chapters that cover writing about interactions, writing about event history analysis, writing about multilevel models, and the “Goldilocks principle” for choosing the right size contrast for interpreting results for different variables. In addition, she has updated or added numerous examples, while retaining her clear voice and focus on writers thinking critically about their intended audience and objective. Online podcasts, templates, and an updated study guide will help readers apply skills from the book to their own projects and courses.

This continues to be the only book that brings together all of the steps involved in communicating findings based on multivariate analysis—finding data, creating variables, estimating statistical models, calculating overall effects, organizing ideas, designing tables and charts, and writing prose—in a single volume. When aligned with Miller’s twelve fundamental principles for quantitative writing, this approach will empower readers—whether students or experienced researchers—to communicate their findings clearly and effectively.

AUTHOR BIOGRAPHY

Jane E. Miller is research professor at the Institute for Health, Health Care Policy and Aging Research and professor in the Edward J. Bloustein School of Planning and Public Policy at Rutgers, the State University of New Jersey. Miller also serves as the faculty director of the Robert Wood Johnson Foundation–funded Project L/EARN research training program. She is the author of The Chicago Guide to Writing about Numbers.

REVIEWS

"Miller is no stranger to statistical literacy and quantitative communication. Her previous publications and her experience with teaching research methods benefit this volume’s expansion of the first edition. . . . Recommended."
— Choice

TABLE OF CONTENTS

Tables

Figures

Boxes

Preface

Acknowledgments

A Note on the E-Book

1. Introduction

Part I. Principles

2. Seven Basic Principles

3. Causality, Statistical Significance, and Substantive Significance

4. Five More Technical Principles

Part II. Tools

5. Creating Effective Tables

6. Creating Effective Charts

7. Choosing Effective Examples and Analogies

8. Basic Types of Quantitative Comparisons

9. Quantitative Comparisons for Multivariate Models

10. The “Goldilocks Problem” in Multivariate Regression

11. Choosing How to Present Statistical Test Results

Part III. Pulling It All Together

12. Writing Introductions, Conclusions, and Abstracts

13. Writing about Data and Methods

14. Writing about Distributions and Associations

15. Writing about Multivariate Models

16. Writing about Interactions

17. Writing about Event History Analysis

18. Writing about Hierarchical Linear Models

19. Speaking about Multivariate Analyses

20. Writing for Applied Audiences

Appendix A. Implementing “Generalization, Example, Exceptions” (GEE)

Appendix B. Translating Statistical Output into Table and Text

Appendix C. Terminology for Common Types of Multivariate Models

Appendix D. Using a Spreadsheet forCalculations

Appendix E. Comparison of Research Papers, Presentations, and Posters

Notes

Reference List

Index