Qualitative Analysis

The Important Role of “Buckets” in Qualitative Data Analysis

An earlier article in Research Design Review“Finding Connections & Making Sense of Qualitative Data” – discusses the idea that a quality approach to a qualitative research design incorporates a carefully considered plan for analyzing, and making sense of, the data in order to produce outcomes that are ultimately useful to the users of the research. Specifically, this article touches on the six recommended steps in the analysis process.* These steps might be thought of as a variation of the classic Braun & Clarke (2006) thematic analysis scheme in that the researcher begins by selecting a unit of analysis (and thus becoming familiar with the data) which is then followed by a coding process.

Unique to the six-step process outlined in the earlier RDR article is the step that comes after coding. Rather than immediately digging into the codes searching for themes, it is recommended that the researcher look through the codes to identify categories. These categories basically represent buckets of codes that are deemed to share a certain underlying construct or meaning. In the end, the researcher is left with any number of buckets filled with a few or many codes from which the researcher can identify patterns or themes in the data overall. Importantly, any of the codes within a category or bucket can (and probably will) be used to define more than one theme.

As an example, consider an in-depth interview study with financial managers of a large non-profit organization concerning their key considerations when selecting financial service providers. After the completion of 35 interviews, the researcher absorbs the content, selects the unit of analysis (the entire interview), and develops 75-100 descriptive codes. In the next phase of the process the researcher combs through the codes looking for participants’ thoughts/comments that convey similar broad meaning related to the research question(s). In doing so, Read Full Text

qualitative research design articles

Research Design Review currently includes 180 articles concerning quantitative and qualitative research design issues.  As in recent years, the articles published in 2017 generally revolved around qualitative research, addressing the many concerns in qualitative research design and ways to help the researcher achieve quality outcomes throughout the research process.

“Qualitative research design: A collection of articles from Research Design Review published in 2017″ is a compilation of the 20 articles in 2017 pertaining to a wide variety of qualitative research design issues:

The Use of Quotes & Bringing Transparency to Qualitative Analysis

The use of quotes or verbatims from participants is a typical and necessary component to any qualitative research report. It is by revealing participants’ exact language that the researcher helps the user of the research to understand the key takeaways by clarifying through illustration the essential points of the researcher’s interpretations. The idea is not to display an extensive list of what people said but rather provide quotes that have been carefully selected for being the most descriptive or explanatory of the researcher’s conceptual interpretation of the data. As Susan Morrow has written

“An overemphasis on the researcher’s interpretations at the cost of participant quotes will leave the reader in doubt as to just where the interpretations came from [however] an excess of quotes will cause the reader to become lost in the morass of stories.” (Morrow, 2005, p. 256)

By embedding carefully chosen extracts from participants’ words in the final document, the researcher uniquely gives participants a voice in the outcomes while contributing to the credibility – and transparency – of the research. In essence, the use of verbatims gives the users of the research a peek into the analyst’s codebook by Read Full Text