Partial book profile
The Coding Manual for Qualitative Researchers
A comprehensive reference manual that profiles 35 distinct methods for coding qualitative data and guides researchers through first and second cycle analytic processes toward categories, themes, concepts, and theory.
The full book profile is not available yet.
What it’s about
The Coding Manual for Qualitative Researchers is the field's definitive repertoire of coding techniques, serving as an indispensable companion for students and seasoned scholars alike. Rather than prescribing a single methodology, Johnny Saldana assembles and explains a diverse toolkit of coding methods—from In Vivo and Process Coding to Dramaturgical, Versus, and Causation Coding—each with sources, descriptions, applications, examples, and analytic follow-ups. The manual demystifies how raw interview transcripts, field notes, documents, and visual data are transformed into codes, then organized into categories, themes, and ultimately theory. With its mentorship tone, extensive citations, and pragmatic eclecticism, the book empowers readers to select the right analytic tool for the right job, write reflective analytic memos, and transition confidently from initial coding through final write-up.
The through-line
- Who it’s for
- A qualitative researcher—often a graduate student, dissertation writer, or scholar across disciplines—who has collected interview transcripts, field notes, documents, or visual data and wants to analyze them rigorously and meaningfully.
- The problem
- The researcher faces a voluminous, messy body of qualitative data and does not know which coding methods to use or how to systematically transform raw data into credible findings. The researcher feels overwhelmed, anxious, and fearful about 'getting it right,' uncertain whether they are doing the analysis correctly or learning anything new.
- The plan
- Understand what codes and coding are and the foundations of qualitative analysis.
- Learn fundamental coding techniques, data layout, and analytic memo writing.
- Select appropriate first cycle coding method(s) from the profiled repertoire based on your study's questions and goals.
- Apply, recode, and refine codes while writing concurrent analytic memos.
- Transition to second cycle coding methods to develop categories, themes, concepts, and theory.
- The payoff
- The researcher achieves categorical, thematic, conceptual, and/or theoretical organization of their data. · The researcher experiences new discoveries, insights, and connections about participants, processes, and phenomena. · The researcher produces a credible, trustworthy, and insightful analysis and write-up grounded in the data.
See our guide
- Do Qualitative Research And Coding Well →
- The Behavioral Science Underneath It All →
- Understand Human Behavior From The Foundational Canon →
- Build A People Analytics Function →
- Deal With Burnout, Stress And Turnover →
- Make A Decision Your Biases Won't Wreck →
- Change A Behaviour That Won't Budge →
- Influence People Without Manipulating Them →
- Motivate People Without Bribing Them →
- Design The Organization And Change It →
- Study People And Organizations With Scientific Rigor →
- Build A Team People Speak Up In →
- Do Research That Holds Up →
- Design Surveys People Answer Honestly →
- Understand What Drives Individual Performance →
Related profiles we’ve built
Additional reading
- Qualitative Data Analysis: A Methods Sourcebook · Matthew B. Miles, A. Michael Huberman, & Johnny Saldaña
The author refers to this book, which he co-authored, as the 'cousin' to The Coding Manual. It is presented as a foundational and more expansive resource covering a broader range of qualitative analysis methods beyond coding, especially data display.
- Constructing Grounded Theory · Kathy Charmaz
Charmaz is cited extensively as a primary source for constructivist grounded theory. Her work provides the foundation for several key methods detailed in the manual, including Initial Coding, Focused Coding, and the central role of analytic memoing.
- Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory · Juliet Corbin & Anselm Strauss
This is a foundational text for classic grounded theory. Saldaña references it repeatedly for core concepts like Axial Coding, the development of a central/core category, and the procedural steps for building theory from data.
- The Presentation of Self in Everyday Life · Erving Goffman
Goffman's work provides the theoretical foundation for Dramaturgical Coding. His concepts of social life as a performance, actors managing impressions, and the distinction between frontstage and backstage behavior are central to this analytical approach.
- Metaphors We Live By · George Lakoff & Mark Johnson
This book is the key source for Metaphor Coding. It establishes the principle that metaphor is not just a literary device but a fundamental part of everyday thought and language, providing a conceptual basis for analyzing participant metaphors.
Featured in these guides
- Understand Human Behavior From The Foundational Canon →Cited source
- The Behavioral Science Underneath It All →Cited source
- Build A People Analytics Function →Cited source
- Deal With Burnout, Stress And Turnover →Cited source
- Make A Decision Your Biases Won't Wreck →Cited source
- Change A Behaviour That Won't Budge →Cited source
- Influence People Without Manipulating Them →Cited source
- Motivate People Without Bribing Them →Cited source
- Design The Organization And Change It →Cited source
- Study People And Organizations With Scientific Rigor →Cited source
- Build A Team People Speak Up In →Cited source
- Do Research That Holds Up →Cited source
- Design Surveys People Answer Honestly →Cited source
- Understand What Drives Individual Performance →Cited source
Co-cited books
- Obedience to Authority (Perennial Classics)
- Predictably Irrational, Revised and Expanded Edition · Dan Ariely
- Thinking, Fast and Slow · Daniel Kahneman
- Cultures and Organizations_ Software of the Mind, Third Edition
- Fundamentals of Social Research · Mutea Rukwaru
- The Lucifer Effect: Understanding How Good People Turn Evil
- One hundred years of attrition research (2017)_OCR
- Leading Teams · J. Richard Hackman