What are the most effective methods to code and analyze data for a particular study? This thoughtful and engaging book reviews the selection criteria for coding and analyzing any set of data—whether qualitative, quantitative, mixed, or visual. The authors systematically explain when to use verbal, numerical, graphic, or combined codes, and when to use qualitative, quantitative, graphic, or mixed-methods modes of analysis. Chapters on each topic are organized so that researchers can read them sequentially or can easily "flip and find" answers to specific questions. Nontechnical discussions of cutting-edge approaches—illustrated with real-world examples—emphasize how to choose (rather than how to implement) the various analyses. The book shows how using the right analysis methods leads to more justifiable conclusions and more persuasive presentations of research results.
Useful features for teaching or self-study:
Chapter-opening preview boxes that highlight useful topics addressed.
End-of-chapter summary tables recapping the 'dos and don'ts' and advantages and disadvantages of each analytic technique.
Annotated suggestions for further reading and technical resources on each topic.
See also Vogt et al.'s When to Use What Research Design, which addresses the design and sampling decisions that occur prior to data collection.
“This is the first book I've seen that goes into depth about coding, which is sorely needed. It also does an excellent job of discussing analysis and interpretation at a conceptual level, while providing enough guidance on where to go to get the needed technical assistance. The way the authors compare and contrast quantitative and qualitative methods, approaches, and ways of thinking is particularly strong and well balanced.”
—Marji Erickson Warfield, PhD, Heller School for Social Policy and Management, Brandeis University
“This is a comprehensive resource that delivers what the title promises and more. It provides a great introduction to nearly all data-analytic methods currently utilized by social scientists, and very effectively guides the reader to more in-depth treatments of the subject matter.”
—Ryan Spohn, PhD, University of Nebraska at Omaha, School of Criminology and Criminal Justice
“A field guide for researchers who are looking for detailed discussions of the choices they have to make as they work through the research process, whether they are taking a quantitative, qualitative, or combined approach. This isn't a 'how-to' in terms of analyses, but more of a 'here's what to consider' book. The tone is at once casual and professional, incorporating real-world examples and occasional humor. The authors have their fingers on the pulse of the field and clearly explain complex ideas.”
—Theresa DiDonato, PhD, Department of Psychology, Loyola University Maryland
“A useful text. Many students are stymied by data analysis; they think that you just feed data into some software, and viola! I recently told a student that saying a software package will analyze your data is akin to saying Word will write your dissertation. This book gives students data analysis options so they can choose the approach most appropriate for the specific research design.”
—Janet Salmons, PhD, School of Business and Technology, Capella University
“The authors are masterful writers who combine depth and accessibility.”
—Jerrell C. Cassady, PhD, Department of Educational Psychology, Ball State University
“This book exposes readers to a breadth of coding and analysis considerations for both quantitative and qualitative data. The goal is to teach the reader when it is appropriate to use the various techniques and where to look to learn more. The authors provide a solid foundation of knowledge for navigating a research world where both quantitative and qualitative approaches are valued and necessary. I would definitely use this book in courses. For professional use, I would consult it for areas I am not as familiar with, or to provide resources for students. I particularly enjoyed the non-statistical examples used to explain concepts; they are helpful and make the book easier and more enjoyable to read.”
—Tracey LaPierre, PhD, Department of Sociology, University of Kansas