The purpose of this article is to provide an overview of some of the principles of data analysis used in qualitative research such as coding, interrater reliability, and thematic analysis. I focused on the challenges that I experienced as a first-time qualitative researcher during the course of my dissertation, in the hope that how I addressed those difficulties will better prepare other investigators planning endeavors into this area of research. One of the first challenges I encountered was the dearth of information regarding the details of qualitative data analysis. While my text books explained the general philosophies of the interpretive tradition and its theoretical groundings, I found few published studies where authors actually explained the details pertaining to exactly how they arrived at their findings. Some authors even confirmed my own experience that few published studies described processes such as coding and methods to evaluate interrater reliability. Herein, I share the sources of information that I did find and the methods that I used to address these challenges. I also discuss issues of trustworthiness and how matters of objectivity and reliability can be addressed within the naturalistic paradigm.


Qualitative Research Data Analysis, Coding, Interrater Reliability, Thematic Analysis

Author Bio(s)

I currently serve as a member of the Biomedical Research Alliance of New York (BRANY) IRB, responsible for the review of research protocols. I also serve as a research compliance auditor, responsible for reviews of investigators’ sites, to ensure the conduct of research is in compliance with federal regulations and ethical guidelines. Correspondence regarding this article can be addressed directly to: mbelotto@brany.com.

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Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 International License.





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