Über die Autorin bzw. den Autor

Auszug. © Genehmigter Nachdruck. Alle Rechte vorbehalten.

The Chicago Guide to Writing about Multivariate Analysis

The University of Chicago Press

Contents

List of Tables...................................................................................xiList of Figures..................................................................................xiiiList of Boxes....................................................................................xviiPreface..........................................................................................xixAcknowledgments..................................................................................xxi1. Introduction..................................................................................1PART I. PRINCIPLES2. Seven Basic Principles........................................................................133. Causality, Statistical Significance, and Substantive Significance.............................344. Five More Technical Principles................................................................50PART II. TOOLS5. Creating Effective Tables.....................................................................816. Creating Effective Charts.....................................................................1207. Choosing Effective Examples and Analogies.....................................................1678. Basic Types of Quantitative Comparisons.......................................................1849. Quantitative Comparisons for Multivariate Models..............................................20710. Choosing How to Present Statistical Test Results.............................................231PART III. PULLING IT ALL TOGETHER11. Writing Introductions, Conclusions, and Abstracts............................................25712. Writing about Data and Methods...............................................................27213. Writing about Distributions and Associations.................................................30114. Writing about Multivariate Models............................................................31715. Speaking about Multivariate Analyses.........................................................34916. Writing for Applied Audiences................................................................380Appendix A. Implementing "Generalization, Example, Exceptions" (GEE).............................407Appendix B. Translating Statistical Output into Table and Text...................................417Appendix C. Terminology for Ordinary Least Squares (OLS) and Logistic Models.....................423Appendix D. Using a Spreadsheet for Calculations.................................................433Notes............................................................................................439Reference List...................................................................................445Index............................................................................................457

Chapter One

Writing about multivariate analyses is a surprisingly common task. Results of ordinary least squares (OLS) and logistic regression models inform decisions of government agencies, businesses, and individuals. In everyday life, you encounter forecasts about inflation, unemployment, and interest rates in the newspaper, predictions of hurricanes' timing and location in television weather reports, and advice about behaviors and medications to reduce heart disease risk in magazines and health pamphlets. In many professional fields, multivariate analyses are included in research papers, grant proposals, policy briefs, and consultant's reports. Economists and meteorologists, health researchers and college professors, graduate students and policy analysts all need to write about multivariate models for both statistical and nonstatistical audiences. In each of these situations, writers must succinctly and clearly convey quantitative concepts and facts.

Despite this apparently widespread need, few people are formally trained to write about numbers, let alone multivariate analyses. Communications specialists learn to write for varied audiences, but rarely are taught specifically to deal with statistical analyses. Statisticians and researchers learn to estimate regression models and interpret the findings, but rarely are taught to describe them in ways that are comprehensible to readers with different levels of quantitative expertise or interest. I have seen poor communication of statistical findings at all levels of training and experience, from papers by students who were stymied about how to put numbers into sentences, to presentations by consultants, policy analysts, and applied scientists, to publications by experienced researchers in elite peer-reviewed journals. This book is intended to bridge the gap between correct multivariate analysis and good expository writing, taking into account your intended audience and objective.

* AUDIENCES FOR MULTIVARIATE ANALYSES

Results of multivariate analyses are of interest to a spectrum of audiences, including:

legislators, members of nonprofit organizations, the general public, and other "applied audiences" who may have little statistical training but want to understand and apply results of multivariate analyses about issues that matter to them;

readers of a professional journal in your field who often vary substantially in their familiarity with multivariate models;

reviewers for a grant proposal or article involving a multivariate analysis, some of whom are experts on your topic but not the methods, others of whom are experts in advanced statistical methods but not your topic;

an audience at an academic seminar or workshop where everyone works with various regression methods and delights in debating statistical assumptions and dissecting equations.

Clearly, these audiences require very different approaches to writing about multivariate analyses.

Writing for a Statistical Audience

When writing for statistically trained readers, explain not only the methods and findings but also the reasons a multivariate model is needed for your particular study and how the findings add to the body of knowledge on the topic. I have read many papers and sat through many presentations about statistical analyses that focused almost solely on equations and computer output full of acronyms and statistical jargon. Even if your audience is well versed in multivariate techniques, do not assume that they understand why those methods are appropriate for your research question and data. And it behooves you to make it as easy as possible for reviewers of your paper or grant proposal to understand the point of your analysis and how it advances previous research.

Another important objective is to avoid a "teaching" style as you write about multivariate analyses. Although professional journals usually require that you report the detailed statistical results to show the basis for your conclusions, reading your paper should not feel like a refresher course in regression analysis. Do not make your readers slog through every logical step of the statistical tests or leave it to them to interpret every number for themselves. Instead, ask and answer the research question, using the results of your analysis as quantitative evidence in your overall narrative.

Writing for a Nonstatistical Audience

Although researchers typically learn to...