Qualitative and Mixed Methods Data Analysis Using Dedoose

Dr. Michelle Salmona serves as President (co-founder) of the Institute for Mixed Methods Research (IMMR) with an academic appointment as Adjunct Professor at the University of Canberra, Australia. She has authored multiple books and academic papers including her book co-authored with Dan Kaczynski and Eli Lieber Qualitative and Mixed Methods Data Analysis Using Dedoose: A Practical Approach for Research Across the Social Sciences. Michelle has been working for over 20 years as a mentor in writing about strong research, and a teacher in qualitative data analysis and the use of Qualitative Data Analysis Software (QDAS). In addition, she is a credentialed project management professional (PMP) and senior fellow of the Higher Education Academy, United Kingdom. Michelle is a specialist in qualitative and mixed methods research design and analysis, and works as an international consultant in: program evaluation; research design; and mixed-methods and qualitative data analysis using digital tools. Her research focus is to better understand how to support doctoral success and strengthen the research process; and build data-driven decision-making capacity through technological innovation. Recent research includes exploring the changing practices of qualitative research during the dissertation phase of doctoral studies, and investigating how we bring learning into the use of technology during the research process. Michelle is currently working on projects with researchers from education, information systems, business communication, leadership, and finance. Dr. Eli Lieber is an interdisciplinary social scientist, methodologist, and data analyst.  He has spent over 20 years at the University of California, Los Angeles focused on advancing our thinking about and strategically implementing qualitative and mixed methods approaches in social science research.  Initially trained as a quantitative psychologist, he soon began working with colleagues from other social science disciplines and came to appreciate the deep importance and role in qualitative perspectives.  From a practical view, he believes that the informed integration of methods, study design, and the data generated produce more comprehensive and robust research findings than those from more method-centric approaches. Dr. Lieber’s recent work has focused on the continued development of mixed methods strategies and technologies.  Eli is particularly interested in what we do with all the data we gather: How can data be integrated and what evolving technologies can make our research and evaluation work and findings more efficient, effective, and sustainable? Eli looks forward to his work with Institute for Mixed Methods Research (IMMR) colleagues—a truly global and diverse group of individuals.  The IMMR mission will be an ongoing service to building methodological capacity, relationship building, engagement and communication regarding evolving mixed methods work, and bringing the deep experience of IMMR associates into the service of others employing these practices.  Dr. Lieber is optimistic about how mixed methods research and IMMR can advance social science through engaging with colleagues directly, through connections within larger institutions organizations, and through the forging of strategic partnerships. Professor Dan Kaczynski is Professor Emeritus at Central Michigan University and a senior research fellow at the IMMR. He is currently an adjunct professor supervising doctoral candidates at the University of Canberra, Australia. His research interests promote technological innovations in qualitative and mixed meth­ods data analysis in the social sciences in the United States and Australia. Dan is a program evaluation consultant and has more than 20 years’ experience conducting state, national, and international evaluations. Leadership roles include K-12 and higher education administration and research center director with extensive experience as principal investigator of more than $35 million in grant awards. His work has been shared professionally with more than 250 professional presentations nationally and internationally. He has written more than 50 published research articles and eight books and book chapters. In addition, he has supervised over 100 doctoral dissertations and professional specialist theses. 

Foreword by Lyn Richards
Preface
Acknowledgments
Glossary: Dedoose Common Terms
About the Authors
PART I FOUNDATIONS OF MIXED METHODS RESEARCH
Chapter 1 Using Mixed Methods and Dedoose
1.1 About This Book
1.2 Mixed Methods and Mixed Paradigms
1.3 Using Cloud Technology to Support Mixed Methods Research
1.4 What Is Dedoose?
1.5 Dedoose: A Historical Journey
Chapter 2 Adopting Dedoose
2.1 Successful Adoption of Digital Tools
2.2 Framing the Purpose and Focus
2.3 Dedoose: Starting Your Project
2.4 Case Study: Using the Five-Level QDA® Method With Dedoose
Chapter 3 Bringing Data Into Dedoose
3.1 Gathering Mixed Data
3.2 Numbers as Data
3.3 Memos as Data
3.4 Case Study: Incorporating Mixed Analysis Into Your Study
3.5 Conclusion
Appendix: Types of Interview Data
PART II DATA INTERACTION AND ANALYSIS
Chapter 4 Teamwork Analysis Techniques
4.1 Team Management
4.2 Collaborative Interpretations
4.3 Coding in Teams
4.4 Bringing Procedures Into the Dedoose Environment
4.5 Team Conduct Rules
4.6 Case Study: Large-Scale, Multilanguage, Cross-Cultural Analysis With Dedoose
4.7 Conclusion
Chapter 5 Qualitative Analysis
5.1 Qualitative Analysis: Looking for Quality
5.2 Working With Codes
5.3 Case Study: Using Dedoose for a Multisite Study
5.4 Conclusion
Chapter 6 Designing Mixed Methods Analysis
6.1 Identifying Analysis Strategies
6.2 Using Descriptors
6.3 Topic Modeling
6.4 Case Study: Integrating Mixed Data in a Longitudinal Study
6.5 Conclusion
Chapter 7 Managing Complex Mixed Methods Analysis
7.1 Recognizing and Managing Complexity in Analysis
7.2 Data Complexity in Your Project
7.3 Using Visualization Tools for Analysis
7.4 Moving Through and Filtering Your Data
7.5 Case Study: Complex Yet Manageable—the Organizational Genius of Dedoose
7.6 Conclusion
Chapter 8 Working With Numbers in Dedoose: Statistics, Tabling, and Charting for Numbers, Weights, and Option List Field Data
8.1. Background/Introduction
8.2 Charts, Tables, and Plots for Individual Fields or Code Weights
8.3 Charts, Tables, Plots, and Analyses for Pairs of Fields/Code Weights
8.4 Summary
PART III REPORTING CREDIBLE RESULTS AND SHARING FINDINGS
Chapter 9 Reporting Your Findings
9.1 Reaching Your Audience
9.2 Mixed Methods Procedural Checklist
9.3 Case Study: Reporting to Multiple Audiences
Chapter 10 Sharing Data With a Larger Audience
10.1 Reaching a Larger Audience
10.2 Case Study: Sharing Qualitative Social Science Data
10.3 Changing Reporting Practices: Open Access
10.4 Final Word
Closing Remarks by Thomas S. Weisner
References
Index