Qualitative Data Analysis: An Expanded Sourcebook
The latest edition of this best-selling textbook by Miles and Huberman not only is considerably expanded in content, but is now available in paperback. Bringing the art of qualitative analysis up-to-date, this edition adds hundreds of new techniques, ideas and references developed in the past decade. The increase in the use of computers in qualitative analysis is also reflected in this volume. There is an extensive appendix on criteria to choose from among the currently available analysis packages. Through examples from a host of social science and professional disciplines, Qualitative Data Analysis remains the most comprehensive and complete treatment of this topic currently available to scholars and applied researchers.
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I have found this book to be invaluable as an emerging researcher and PhD Candidate. The book helps to demystify features of qualitative research with the use of an array of examples to highlight pertinent points. A draw back is the date of the text, and as such an updated edition would be invaluable. Definitely a book I would use within my own teaching of research to undergraduate and postgraduate students.
If you enjoy a positivistic/post-positivistic approach to qualitative research, then this is the book for you! I, on the other hand, think this is probably the most archaic textbook available that deals with qualitative data analysis. How can the authors even consider this book remotely related to qualitative research? Most of their procedures/processes are 'quantitative-like' (as most of the processes are deductive in nature), which is not what qualitative research is about. It's approach is very mechanical, and it seems as if the authors are trying to appeal to quantitative researchers based on the methods and terms used. If you truly want to conduct a constructivist, qualitative study, then I suggest you look elsewhere.
Some Rules of Thumb
A Tactics for Generating Meaning
Ethical Issues in Analysis 288 References 318
Innovation a workexperience program
PredictorOutcome Consequences Matrix
Additional Factors Related to Early Implementation