The Chicago Guide to Writing about Multivariate Analysis, Second Edition
The Chicago Guide to Writing about Multivariate Analysis, Second Edition

Author: Jane E. Miller

Publisher: University of Chicago Press

Published: 2013-09-26

Total Pages: 576

ISBN-13: 022603819X

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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.

The Chicago Guide to Writing About Numbers
The Chicago Guide to Writing About Numbers

Author: Jane E. Miller

Publisher: University of Chicago Press

Published: 2015-04-09

Total Pages: 431

ISBN-13: 022618580X

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For students, scientists, journalists and others, a comprehensive guide to communicating data clearly and effectively. Acclaimed by scientists, journalists, faculty, and students, The Chicago Guide to Writing about Numbers has helped thousands communicate data clearly and effectively. It offers a much-needed bridge between good quantitative analysis and clear expository writing, using straightforward principles and efficient prose. With this new edition, Jane Miller draws on a decade of additional experience and research, expanding her advice on reaching everyday audiences and further integrating non-print formats. Miller, an experienced teacher of research methods, statistics, and research writing, opens by introducing a set of basic principles for writing about numbers, then presents a toolkit of techniques that can be applied to prose, tables, charts, and presentations. She emphasizes flexibility, showing how different approaches work for different kinds of data and different types of audiences. The second edition adds a chapter on writing about numbers for lay audiences, explaining how to avoid overwhelming readers with jargon and technical issues. Also new is an appendix comparing the contents and formats of speeches, research posters, and papers, to teach writers how to create all three types of communication without starting each from scratch. An expanded companion website includes new multimedia resources such as slide shows and podcasts that illustrate the concepts and techniques, along with an updated study guide of problem sets and suggested course extensions. This continues to be the only book that brings together all the tasks that go into writing about numbers, integrating advice on finding data, calculating statistics, organizing ideas, designing tables and charts, and writing prose all in one volume. Field-tested with students and professionals alike, this is the go-to guide for everyone who writes or speaks about numbers.

Indexing Books, Second Edition
Indexing Books, Second Edition

Author: Nancy C. Mulvany

Publisher: University of Chicago Press

Published: 2009-11-15

Total Pages: 349

ISBN-13: 0226550176

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Since 1994, Nancy Mulvany's Indexing Books has been the gold standard for thousands of professional indexers, editors, and authors. This long-awaited second edition, expanded and completely updated, will be equally revered. Like its predecessor, this edition of Indexing Books offers comprehensive, reliable treatment of indexing principles and practices relevant to authors and indexers alike. In addition to practical advice, the book presents a big-picture perspective on the nature and purpose of indexes and their role in published works. New to this edition are discussions of "information overload" and the role of the index, open-system versus closed-system indexing, electronic submission and display of indexes, and trends in software development, among other topics. Mulvany is equally comfortable focusing on the nuts and bolts of indexing—how to determine what is indexable, how to decide the depth of an index, and how to work with publisher instructions—and broadly surveying important sources of indexing guidelines such as The Chicago Manual of Style, Sun Microsystems, Oxford University Press, NISO TR03, and ISO 999. Authors will appreciate Mulvany's in-depth consideration of the costs and benefits of preparing one's own index versus hiring a professional, while professional indexers will value Mulvany's insights into computer-aided indexing. Helpful appendixes include resources for indexers, a worksheet for general index specifications, and a bibliography of sources to consult for further information on a range of topics. Indexing Books is both a practical guide and a manifesto about the vital role of the human-crafted index in the Information Age. As the standard indexing reference, it belongs on the shelves of everyone involved in writing and publishing nonfiction books.

Applied Missing Data Analysis
Applied Missing Data Analysis

Author: Craig K. Enders

Publisher: Guilford Press

Published: 2010-04-23

Total Pages: 401

ISBN-13: 1606236393

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Walking readers step by step through complex concepts, this book translates missing data techniques into something that applied researchers and graduate students can understand and utilize in their own research. Enders explains the rationale and procedural details for maximum likelihood estimation, Bayesian estimation, multiple imputation, and models for handling missing not at random (MNAR) data. Easy-to-follow examples and small simulated data sets illustrate the techniques and clarify the underlying principles. The companion website includes data files and syntax for the examples in the book as well as up-to-date information on software. The book is accessible to substantive researchers while providing a level of detail that will satisfy quantitative specialists. This book will appeal to researchers and graduate students in psychology, education, management, family studies, public health, sociology, and political science. It will also serve as a supplemental text for doctoral-level courses or seminars in advanced quantitative methods, survey analysis, longitudinal data analysis, and multilevel modeling, and as a primary text for doctoral-level courses or seminars in missing data.

Multilevel Analysis
Multilevel Analysis

Author: Joop J. Hox

Publisher: Routledge

Published: 2010-09-13

Total Pages: 564

ISBN-13: 1136975349

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This practical introduction helps readers apply multilevel techniques to their research. Noted as an accessible introduction, the book also includes advanced extensions, making it useful as both an introduction and as a reference to students, researchers, and methodologists. Basic models and examples are discussed in non-technical terms with an emphasis on understanding the methodological and statistical issues involved in using these models. The estimation and interpretation of multilevel models is demonstrated using realistic examples from various disciplines. For example, readers will find data sets on stress in hospitals, GPA scores, survey responses, street safety, epilepsy, divorce, and sociometric scores, to name a few. The data sets are available on the website in SPSS, HLM, MLwiN, LISREL and/or Mplus files. Readers are introduced to both the multilevel regression model and multilevel structural models. Highlights of the second edition include: Two new chapters—one on multilevel models for ordinal and count data (Ch. 7) and another on multilevel survival analysis (Ch. 8). Thoroughly updated chapters on multilevel structural equation modeling that reflect the enormous technical progress of the last few years. The addition of some simpler examples to help the novice, whilst the more complex examples that combine more than one problem have been retained. A new section on multivariate meta-analysis (Ch. 11). Expanded discussions of covariance structures across time and analyzing longitudinal data where no trend is expected. Expanded chapter on the logistic model for dichotomous data and proportions with new estimation methods. An updated website at http://www.joophox.net/ with data sets for all the text examples and up-to-date screen shots and PowerPoint slides for instructors. Ideal for introductory courses on multilevel modeling and/or ones that introduce this topic in some detail taught in a variety of disciplines including: psychology, education, sociology, the health sciences, and business. The advanced extensions also make this a favorite resource for researchers and methodologists in these disciplines. A basic understanding of ANOVA and multiple regression is assumed. The section on multilevel structural equation models assumes a basic understanding of SEM.

Research Methods in Practice
Research Methods in Practice

Author: Dahlia K. Remler

Publisher: SAGE Publications

Published: 2021-08-24

Total Pages: 650

ISBN-13: 1544318405

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Thoroughly updated to reflect changes in both research and methods, this Third Edition of Remler and Van Ryzin’s innovative, standard-setting text is imbued with a deep commitment to making social and policy research methods accessible and meaningful. Research Methods in Practice: Strategies for Description and Causation motivates readers to examine the logic and limits of social science research from academic journals and government reports. A central theme of causation versus description runs through the text, emphasizing the idea that causal research is essential to understanding the origins of social problems and their potential solutions. Readers will find excitement in the research experience as the best hope for improving the world in which we live, while also acknowledging the trade-offs and uncertainties in real-world research.

The Chicago Guide to Grammar, Usage, and Punctuation
The Chicago Guide to Grammar, Usage, and Punctuation

Author: Bryan A. Garner

Publisher: Univ of Chicago+ORM

Published: 2016-05-16

Total Pages: 680

ISBN-13: 022619129X

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The authoritative guide to using the English language effectively, from “the greatest writer on grammar and usage that this country has ever produced” (David Yerkes, Columbia University). The author of The Chicago Manual of Style’s popular “Grammar and Usage” chapter, Bryan A. Garner is renowned for explaining the vagaries of English with absolute precision and utmost clarity. With The Chicago Guide to Grammar, Usage, and Punctuation, he has written the definitive guide for writers who want their prose to be both memorable and correct. Garner describes standard literary English—the forms that mark writers and speakers as educated users of the language. He also offers historical context for understanding the development of these forms. The section on grammar explains how the canonical parts of speech came to be identified, while the section on syntax covers the nuances of sentence patterns as well as both traditional sentence diagramming and transformational grammar. The usage section provides an unprecedented trove of empirical evidence in the form of Google Ngrams, diagrams that illustrate the changing prevalence of specific terms over decades and even centuries of English literature. Garner also treats punctuation and word formation, and concludes the book with an exhaustive glossary of grammatical terms and a bibliography of suggested further reading and references. The Chicago Guide to Grammar, Usage, and Punctuation is a magisterial work, the culmination of Garner’s lifelong study of the English language. The result is a landmark resource that will offer clear guidelines to students, writers, and editors alike. “[A manual] for those of us laboring to produce expository prose: nonfiction books, journalistic articles, memorandums, business letters. The conservatism of his advice pushes you to consider audience and occasion, so that you will understand when to follow convention and when you can safely break it.”—John E. McIntyre, Baltimore Sun

An Introduction to Applied Multivariate Analysis with R
An Introduction to Applied Multivariate Analysis with R

Author: Brian Everitt

Publisher: Springer Science & Business Media

Published: 2011-04-23

Total Pages: 284

ISBN-13: 1441996508

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The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings are taken on each of the units in the data set. These units might be human subjects, archaeological artifacts, countries, or a vast variety of other things. In a few cases, it may be sensible to isolate each variable and study it separately, but in most instances all the variables need to be examined simultaneously in order to fully grasp the structure and key features of the data. For this purpose, one or another method of multivariate analysis might be helpful, and it is with such methods that this book is largely concerned. Multivariate analysis includes methods both for describing and exploring such data and for making formal inferences about them. The aim of all the techniques is, in general sense, to display or extract the signal in the data in the presence of noise and to find out what the data show us in the midst of their apparent chaos. An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as much information as possible from the data at hand, particularly as some type of graphical representation, via the R software. Throughout the book, the authors give many examples of R code used to apply the multivariate techniques to multivariate data.