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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 Chicago Guide to Writing About Multivariate Analysis 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.
Preface
Chapter 1 Introduction
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Chapter 2 Seven Basic Principles
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Chapter 3 Causality, Statistical Signifi cance, and Substantive Significance
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Chapter 4 Five More Technical Principles
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Chapter 5 Creating Eff ective Tables
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Chapter 6 Creating Eff ective Charts
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Chapter 7 Choosing Eff ective Examples and Analogies
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Chapter 8 Basic Types of Quantitative Comparisons
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Chapter 9 Quantitative Comparisons for Multivariate Models
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Chapter 10 The “Goldilocks Problem” in Multivariate Regression
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Chapter 11 Choosing How to Present Statistical Test Results
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Chapter 12 Writing Introductions, Conclusions, and Abstracts
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Chapter 13 Writing about Data and Methods
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Chapter 14 Writing about Distributions and Associations
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Chapter 15 Writing about Multivariate Models
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Chapter 16 Writing about Interactions
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Chapter 17 Writing about Event History Analysis
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Chapter 18 Writing about Hierarchical Linear Models
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Chapter 19 Speaking about Multivariate Analyses
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Chapter 20 Writing for Applied Audiences
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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. She is the author of The Chicago Guide to Writing about Numbers.
