Overview

Qualitative and Mixed Methods Data Analysis Using Dedoose® provides both new and experienced researchers with a guided introduction to dealing with the methodological complexity of mixed methods and qualitative inquiry using Dedoose® software.

Full Product Details

Author:   Michelle Salmona ,  Dan Kaczynski ,  Sara E. Grummert
Publisher:   Sage Publications Inc Ebooks
Imprint:   SAGE Publications Inc
Edition:   2nd Revised edition
Weight:   0.680kg
ISBN:  

9781071949931

ISBN 10:   1071949934
Pages:   408
Publication Date:   14 May 2026
Audience:   College/higher education ,  Tertiary & Higher Education
Format:   Paperback
Publisher's Status:   Forthcoming
Availability:   Not yet available  
This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release.

Table of Contents

Foreword by Eli Lieber Preface Acknowledgements Glossary: Dedoose Common Terms About the Authors Part I: Foundations of Research Chapter 1: Introduction 1.1 Overview of the Book 1.2 What is Dedoose? 1.3 Course Adoption 1.4 Dedoose for Literature Review: A Guide for Researchers 1.5 Appendix: Keyboard Shortcuts Chapter 2: Qualitative Data Analysis 2.1 Framing the study 2.2 Aligning Theory to the Analytic Approach 2.3 Getting Started with the Analysis of Raw Data 2.4 Building Connections and Finding Relationships 2.5 Analytic Rabbit holes Chapter 3: Mixed Methods Data Analysis 3.1 Mixed Methods and Mixed Paradigms 3.2 Identifying Mixed Methods Analysis Strategies 3.3 Preparing for Mixed Methods Analysis Chapter 4: Data Management 4.1 Gathering data 4.2 Numbers as data 4.3 Memos as data 4.4 Preparing data for import 4.5 Conclusion Appendix: Types of interview data Part II: Data Interaction and Analysis Chapter 5: Doing Qualitative Analysis in Dedoose 5.1 Working with media and excerpts in Dedoose 5.2 Working with codes in Dedoose 5.3 Memos in Dedoose 5.4 Qualitative coding tips 5.5 Conclusion Chapter 6: Doing Mixed Methods Analysis in Dedoose 6.1 Working with Numeric and Categorical Data 6.2 Recognizing and Managing Complexity in Analysis 6.3 Data Complexity in Your Project 6.4 Mixed methods code tips | Integrating mixed methods data during analysis 6.5 Mixing Qualitative and Quantitative Data by Hannah Calvert 6.6 Conclusion Chapter 7: Analysis Through Visualization 7.1 Using Visualization Tools for Analysis 7.2 Code Charts 7.3 Code and Descriptor Charts 7.4 Descriptor Charts 7.5 Moving Through and Filtering Your Data 7.6 Conclusion Chapter 8: Advanced Tools and Automation in Dedoose 8.1 Advanced Codebook Management 8.2 Text Analytics 8.3 Automation Tools in Dedoose 8.4 Using Artificial Intelligence 8.5 Summary Chapter 9: Teamwork Analysis Techniques 9.1 Team development 9.2 Collaborative Interpretations 9.3 Team Guidelines Chapter 10: Collaborating Successfully in Dedoose 10.1 When to Work with Others 10.2 Approaches to Team Coding in Dedoose 10.3 Developing a Team Coding Process | Tips and Guidelines 10.4 Conclusion 10.5 Appendix | Access Group Categories in Dedoose Conclusion to Part Two: Data Interaction and Analysis Part III: Reporting Credible Results and Sharing Findings Chapter 11: Sharing Data with a Larger Audience 11.1 Reaching a Larger Audience 11.2 Sharing Qualitative Social Science Data by QDR 11.3 Data Anonymization by Hannah Calvert 11.4 Changing Reporting Practices: Open Access 11.5 Conclusion Chapter 12: Reporting Your Findings 12.1 Reaching Your Audience 12.2 Qualitative Methods Procedural Checklist 12.3 Mixed Methods Procedural Checklist 12.4 Reporting to Multiple Audiences 12.5 Effective Research Communication Across Diverse Audiences Chapter 13: Qualitative Analysis and AI: What does the future hold? 13.1 Introduction 13.2 Qualitative Practices Shifting from Past to Present 13.3 AI Adoption in Qualitative Analysis 13.4 An Epistemological Conundrum 13.5 Overcoming Limitations of AI 13.6 Building a Framework for the Future Chapter 14: Ending the Book 14.1 Navigating the Evolving Landscape of Research 14.2 Revisiting Our Path 14.3 Key Takeaways 14.4 The Road Ahead 14.5 Final Word Afterword References Index

Reviews

This book is a wonderful mixture of technical and theoretical knowledge for even the newest Dedoose users! I would trust it with my students and believe it would have a very positive impact on their learning of qualitative methods. -- Colleen Berryessa

Author Information

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. 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. 

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