Selecting the Right Analyses for Your Data Quantitative, Qualitative, and Mixed Methods

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.

User-Friendly Features
*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.

W. Paul Vogt, PhD, is Emeritus Professor of Research Methods and Evaluation at Illinois State University, where he has won both teaching and research awards. Dr. Vogt’s areas of specialization include research design and data analysis, with particular emphasis on combining qualitative, quantitative, and graphic approaches. He is coauthor (with Dianne C. Gardner and Lynne M. Haeffele) of When to Use What Research Design.
 
Elaine R. Vogt, MA, CAS, is certified as a school psychologist in New York and Illinois and has worked as a psychologist in schools and a variety of other public and private institutions. She recently retired from Illinois Wesleyan University, where she taught piano and was a staff accompanist. Ms. Vogt's research interests include cognitive psychology, especially music cognition.
 
Dianne C. Gardner, PhD, is Associate Professor of Educational Administration and Foundations and Research Associate at the Center for the Study of Education Policy at Illinois State University. Dr. Gardner’s research interests include assessment, evaluation of collaborative professional learning systems, qualitative research methodology, and P-20 education systems. She serves as a program evaluator for state- and federally funded education programs.
 
Lynne M. Haeffele, PhD, is Senior Research Associate at the Center for the Study of Education Policy at Illinois State University and also serves as Education Policy Director in the Office of the Illinois Lieutenant Governor. She provides research, evaluation, policy analysis, and management expertise for various state and federal projects in P-20 education. Dr. Haeffele’s research interests include combining research designs, applying research findings to policy and practice, program evaluation, and the topical areas of college readiness and completion, organizational performance, and school-university partnerships.

Preface
General Introduction
I. Coding Data--by Design
1. Coding Survey Data
2. Coding Interview Data
3. Coding Experimental Data
4. Coding Observational Data
5. Coding Archival Data
II. Analysis and Interpretation of Quantitative Data
6. Describing, Exploring, and Visualizing Your Data
7. Inferential Measures and Methods
8. Associational Methods and Analyses
9. Advanced Associational Methods and Analyses
10. Model Selection and Inference: Quantitative Data
III. Analysis and Interpretation of Qualitative and Combined Data
11. Inductive Analyses of Qualitative Data: Ethnographic Approaches and Grounded Theory
12. Deductive Analyses of Qualitative Data: Comparative Case Studies and Qualitative Comparative Analysis
13. Coding and Analyzing Data from Combined and Mixed Designs
14. Common Themes and Diverse Choices