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REVIEW: Qualitative data analysis: An expanded sourcebook

Miles, M.B. & Huberman, A.M. (1994) Qualitative data analysis: an expanded sourcebook (2nd. Ed). London: Sage.


In the first chapter, Miles and Huberman sought to detail the rationale for multiple methods of qualitative research and to explain how these methods can be used to solve problems and set up future research. Their approach encompasses many paradigms of qualitative research, but has some focus in communication research, with a discussion of the importance of understanding interaction and exchange through words and text. A chart on page 6 shows a tree with limbs and offshoot branches of varying kinds of qualitative research. Of the similar charts I have seen with this kind of information, this one is the most complete because it includes participant observation, nonparticipant observation, interview, and archival strategies. These methods include most social science and humanities forms of research and the tree shows how varying methods are related and how they are offshoots of key methods. The four traditions explained here pairs well with John Creswell’s five traditions to give a nearly complete view of qualitative methods.


I say nearly because the chart does not include a visual methods limb, nor branches for case study, semiotics, or visual rhetoric, among others. These methods have a place in qualitative research and belong in this text; I expected to see visual methods, particularly because of the abundance of communication strategies in the text.

However, the strength of this book is in its depth. Miles and Huberman devote considerable attention to the planning, design, and execution of qualitative research.

Chapter 4 provides detailed descriptions of coding schemes and processes. The text drills down to ways researchers can organize data and create a codebook to sort raw information. The author discusses multiple software programs, including Atlas.TI, but the publishing date of this book shows that material is outdated. The book has not been updated since this printing, and the rise of the graphic user interface has changed the way these programs work. While this book is strong in theory and methods, it should not be used to understand coding software.


Researchers can quickly obtain an abundance of data in qualitative inquiry. However, reducing that data into representative sentences can be a challenge The authors discuss the development of models with qualitative data to explain the occurrence of a phenomenon. The collection of data can be coded on multiple levels and then compared within cases and across cases. This dual resonance lends credibility to the findings of qualitative inquiry by showing its placement in the overall world and is transparent enough for outsiders to read the information and draw the same conclusions.


In the end, Miles and Huberman discuss how to translate the resonance of ideas into the understanding of problems. They argue that by considering similar cases with similar outcomes, the researcher can construct a model for how a phenomenon occurs. Further, the researcher can see variations between the multiple models to determine intervening variables. This kind of research can also enhance quantitative research as the researcher will be able to spot possible conflicts and differences to test in the inquiry.


In reading this book, I find many strengths and weaknesses. Like I said above, the strongest part of the book is its explanation of data reduction and analysis in coding the recorded data and then comparing it within the case and then comparing the cases. Second is their discussion of how to use coding schemes and software to find the ultimate resonance to answer research questions and hypotheses, and to find disagreeing information. However, in criticizing this book nearly 20 years after it was written, I see how it is locked into its time. Software has changed. Ideas about what qualitative research can do has changed. Perceptions about the validity of qualitative research has changed. Ultimately, people who read this book should do so to learn how to code data and interpret it, but should realize that qualitative research is widely accepted and ever changing with its methods.

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 © 2019 by Matthew J. Haught

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