Chicago Guide to Writing about Multivariate Analysis

ISBN-10: 0226527875
ISBN-13: 9780226527871
Edition: 2nd 2013
Authors: Jane E. Miller
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Description: The Chicago Guide to Writing about Multivariate Analysisis 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  More...

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Book details

List price: $48.00
Edition: 2nd
Copyright year: 2013
Publisher: University of Chicago Press
Publication date: 7/23/2013
Binding: Paperback
Pages: 560
Size: 6.25" wide x 9.00" long x 1.25" tall
Weight: 1.716
Language: English

The Chicago Guide to Writing about Multivariate Analysisis 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.

List of Tables
List of Figures
List of Boxes
Preface
Acknowledgments
Introduction
Principles
Seven Basic Principles
Causality, Statistical Significance, and Substantive Significance
Five More Technical Principles
Tools
Creating Effective Tables
Creating Effective Charts
Choosing Effective Examples and Analogies
Basic Types of Quantitative Comparisons
Quantitative Comparisons for Multivariate Models
The "Goldilocks Problem" in Multivariate Regression
Choosing How to Present Statistical Test Results
Pulling it All Together
Writing Introductions, Conclusions, and Abstracts
Writing about Data and Methods
Writing about Distributions and Associations
Writing about Multivariate Models
Writing about Interactions
Writing about Event History Analysis
Writing about Hierarchical Linear Models (with Julie Phillips)
Speaking about Multivariate Analyses
Writing for Applied Audiences
Implementing "Generalization, Example, Exceptions" (GEE)
Translating Statistical Output into Table and Text
Terminology for Common Types of Multivariate Models
Using a Spreadsheet for Calculations
Comparison of Research Papers, Speeches, and Posters
Notes
Reference List
Index

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