The contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences. The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better. Key Features: Describes important implicit knowledge to readers: The chapters in this volume explain the important details of seemingly mundane aspects of quantitative research, making them accessible to readers and demonstrating why it is important to pay attention to these details. Compares and contrasts analytic techniques: The book examines instances where there are multiple options for doing things, and make recommendations as to what is the "best" choice—or choices, as what is best often depends on the circumstances. Offers new procedures to update and explicate traditional techniques: The featured scholars present and explain new options for data analysis, discussing the advantages and disadvantages of the new procedures in depth, describing how to perform them, and demonstrating their use. Intended Audience: Representing the vanguard of research methods for the 21st century, this book is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource for practical and sound advice from leading experts in quantitative methods.

Many researchers jump straight from data collection to data analysis without realizing how analyses and hypothesis tests can go profoundly wrong without clean data. This book provides a clear, step-by-step process of examining and cleaning data in order to decrease error rates and increase both the power and replicability of results. Jason W. Osborne, author of Best Practices in Quantitative Methods (SAGE, 2008) provides easily-implemented suggestions that are research-based and will motivate change in practice by empirically demonstrating, for each topic, the benefits of following best practices and the potential consequences of not following these guidelines. If your goal is to do the best research you can do, draw conclusions that are most likely to be accurate representations of the population(s) you wish to speak about, and report results that are most likely to be replicated by other researchers, then this basic guidebook will be indispensible.

This exciting collection is both useful and timely. It clearly lays out the problems, strategies and resources associated with the teaching of quantitative methods in modern universities. Addressing the perceived ′crisis of number′ in a practical and fresh way the book sets out dynamic new approaches to teaching quantitative methods. It offers historical, comparative, analytical reflection and empirical evidence concerning the crisis in contemporary social sciences. Experts from across the social sciences provide a wide range of authoritative insights as well as a number of useful illustrations of strategies and resources designed to help overcome this ′crisis of number′. Each chapter reflects the diversity of backgrounds and approaches within the social sciences making this an interdisciplinary, relevant addition to the subject. The book also: o focuses on innovations in how to teach quantitative research methods o reports on the latest ESRC research projects on teaching quantitative methods o locates itself within current debates about skills for employment. Clear, engaging and original this book will be essential reading for those interested in learning and teaching quantitative methods.

Best Practices in Exploratory Factor Analysis (EFA) is a practitioner-oriented look at this popular and often-misunderstood statistical technique. We avoid formulas and matrix algebra, instead focusing on evidence-based best practices so you can focus on getting the most from your data.Each chapter reviews important concepts, uses real-world data to provide authentic examples of analyses, and provides guidance for interpreting the results of these analysis. Not only does this book clarify often-confusing issues like various extraction techniques, what rotation is really rotating, and how to use parallel analysis and MAP criteria to decide how many factors you have, but it also introduces replication statistics and bootstrap analysis so that you can better understand how precisely your data are helping you estimate population parameters. Bootstrap analysis also informs readers of your work as to the likelihood of replication, which can give you more credibility. At the end of each chapter, the author has recommendations as to how to enhance your mastery of the material, including access to the data sets used in the chapter through his web site. Other resources include syntax and macros for easily incorporating these progressive aspects of exploratory factor analysis into your practice. The web site will also include enrichment activities, answer keys to select exercises, and other resources. The fourth "best practices" book by the author, Best Practices in Exploratory Factor Analysis continues the tradition of clearly-written, accessible guides for those just learning quantitative methods or for those who have been researching for decades.NEW in August 2014! Chapters on factor scores, higher-order factor analysis, and reliability. Chapters: 1 INTRODUCTION TO EXPLORATORY FACTOR ANALYSIS 2 EXTRACTION AND ROTATION 3 SAMPLE SIZE MATTERS 4 REPLICATION STATISTICS IN EFA 5 BOOTSTRAP APPLICATIONS IN EFA 6 DATA CLEANING AND EFA 7 ARE FACTOR SCORES A GOOD IDEA? 8 HIGHER ORDER FACTORS 9 AFTER THE EFA: INTERNAL CONSISTENCY 10 SUMMARY AND CONCLUSIONS

Communication research is evolving and changing in a world of online journals, open-access, and new ways of obtaining data and conducting experiments via the Internet. Although there are generic encyclopedias describing basic social science research methodologies in general, until now there has been no comprehensive A-to-Z reference work exploring methods specific to communication and media studies. Our entries, authored by key figures in the field, focus on special considerations when applied specifically to communication research, accompanied by engaging examples from the literature of communication, journalism, and media studies. Entries cover every step of the research process, from the creative development of research topics and questions to literature reviews, selection of best methods (whether quantitative, qualitative, or mixed) for analyzing research results and publishing research findings, whether in traditional media or via new media outlets. In addition to expected entries covering the basics of theories and methods traditionally used in communication research, other entries discuss important trends influencing the future of that research, including contemporary practical issues students will face in communication professions, the influences of globalization on research, use of new recording technologies in fieldwork, and the challenges and opportunities related to studying online multi-media environments. Email, texting, cellphone video, and blogging are shown not only as topics of research but also as means of collecting and analyzing data. Still other entries delve into considerations of accountability, copyright, confidentiality, data ownership and security, privacy, and other aspects of conducting an ethical research program. Features: 652 signed entries are contained in an authoritative work spanning four volumes available in choice of electronic or print formats. Although organized A-to-Z, front matter includes a Reader’s Guide grouping entries thematically to help students interested in a specific aspect of communication research to more easily locate directly related entries. Back matter includes a Chronology of the development of the field of communication research; a Resource Guide to classic books, journals, and associations; a Glossary introducing the terminology of the field; and a detailed Index. Entries conclude with References/Further Readings and Cross-References to related entries to guide students further in their research journeys. The Index, Reader’s Guide themes, and Cross-References combine to provide robust search-and-browse in the e-version.

Jason W. Osborne’s Best Practices in Logistic Regression provides students with an accessible, applied approach that communicates logistic regression in clear and concise terms. The book effectively leverages readers’ basic intuitive understanding of simple and multiple regression to guide them into a sophisticated mastery of logistic regression. Osborne’s applied approach offers students and instructors a clear perspective, elucidated through practical and engaging tools that encourage student comprehension.

The bestseller that pioneered the comparison of qualitative, quantitative, and mixed methods research design continues in its Fourth Edition to help students and researchers prepare their plan or proposal for a scholarly journal article, dissertation or thesis.