The Chicago Guide to Writing about Multivariate Analysis

by Jane E. Miller

University of Chicago Press, 2005
Cloth: 978-0-226-52782-6 | Paper: 978-0-226-52783-3 | Electronic: 978-0-226-52784-0
DOI: 10.7208/chicago/9780226527840.001.0001

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ABOUT THIS BOOKAUTHOR BIOGRAPHYREVIEWSTABLE OF CONTENTS

ABOUT THIS BOOK

Writing about multivariate analysis is a surprisingly common task. Researchers use these advanced statistical techniques to examine relationships among multiple variables, such as exercise, diet, and heart disease, or to forecast information such as future interest rates or unemployment. Many different people, from social scientists to government agencies to business professionals, depend on the results of multivariate models to inform their decisions. At the same time, many researchers have trouble communicating the purpose and findings of these models. Too often, explanations become bogged down in statistical jargon and technical details, and audiences are left struggling to make sense of both the numbers and their interpretation.

Here, Jane Miller offers much-needed help to academic researchers as well as to analysts who write for general audiences. The Chicago Guide to Writing about Multivariate Analysis brings together advanced statistical methods with good expository writing. Starting with twelve core principles for writing about numbers, Miller goes on to discuss how to use tables, charts, examples, and analogies to write a clear, compelling argument using multivariate results as evidence.

Writers will repeatedly look to this book for guidance on how to express their ideas in scientific papers, grant proposals, speeches, issue briefs, chartbooks, posters, and other documents. Communicating with multivariate models need never appear so complicated again.

AUTHOR BIOGRAPHY

Jane E. Miller is on the faculty at the Institute for Health, Health Care Policy, and Aging Research and the Edward J. Bloustein School of Planning and Public Policy at Rutgers University. She is the author of The Chicago Guide to Writing about Numbers, published by the University of Chicago Press.

REVIEWS

“This is a terrific book that almost everyone writing or talking about multivariate analysis, from undergraduate student to veteran scholar, would find useful.”

— James Trussell, Professor of Economics and Public Affairs and Director, Office of Population Research, Princeton University

“The Chicago Guide to Writing About Multivariate Analysis provides practical guidance to anyone who has to organize and present basic and complex statistical analyses. From presentations to manuscripts, from scientific to lay audiences, from simple concepts to complex ones, this book covers the waterfront of issues with an easy-to-grasp style. The book is loaded with practical examples, often illustrated with poor, better, and best ways to communicate. . . . The value of multivariate analyses lies in a clear understanding of the data, the information gleaned, the meaning, and the implications for research and action. This book should enhance that value for scientists in many disciplines and at all levels and give them greater confidence in the effectiveness of their communication.”

— Steven Teutsch, chief science officer of the Los Angeles County Health Department

“Aimed at people with a concrete grounding in multivariate analysis and other advanced statistical methods, this handbook outlines basic narrative and graphic communication principles and practices for using numeric facts as evidence in a research inquiry. Focusing on both publications and oral presentations, it covers audiences, research questions, summarizing, reviews, and answering ‘so what’ questions—as well as connecting all the dots in between. To assist readers in understanding the ideas, Miller practices what she preaches, keeping text succinct, vocabulary accessible, and examples and analogies easy to relate to. The tome is chock full of ‘Zen moments’.”

— Choice

"The extent of the research and thought that went into this work is clear in the wealth of information presented and the extensive reference citations. Although the information presented may seem basic to highly experienced and specialized scientific writers and editors, they might find it helpful to have it all covered in a single, compact text. Generalist writers and editors will probably find it useful in ensuring that their work includes relevant, well-presented information."

— Edith Paal, Science Editor

“Jane Miller begins by offering her readers a map to help them navigate their way through the maze of multivariate analysis. . . . It will be a useful reference text to all involved with presenting data.”

— Wadia "Wade" Hanna, Public Health

List of Tables

List of Figures

List of Boxes

Preface

Acknowledgment

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. Choosing How to Present Statistical Test Results

Part III. Pulling It All Together

11. Writing Introductions, Conclusions, and Abstracts

12. Writing about Data and Methods

13. Writing about Distributions and Associations

14. Writing about Multivariate Models

15. Speaking about Multivariate Analyses

16. Writing for Applied Audiences

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

Appendix B. Translating Statistical Output into Table and Text

Appendix C. Terminology for Ordinary Least Squares (OLS) and Logistic Models

Appendix D. Using a Spreadsheet for Calculations

Notes

Reference List

Index