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3 Straightforward Methods for Analyzing Qualitative Interview Data
- January 11, 2016
- Posted by: Mike Rucker
- Category: Research
To some qualitative data analysis may seem like a daunting task. Some quantitative researchers openly admit they would not know where to begin if given the job, and that the unfamiliar process scares them a bit. Unlike most quantitative methodologies, qualitative analysis does not follow a formula-like procedure that can be systematically and analytically applied. When we embark on a qualitative journey, we need to be prepared to work in a slightly more intuitive and not always tangible way. But that does not imply qualitative methodology lacks rigor. On the contrary — it just achieves results in a different way to a quantitative study.
Do not let this post’s title fool you, qualitative analysis is not an easy task. Often time-consuming and at times slightly chaotic, the researcher generally never knows where the study will take them. But, hey, that’s also the beauty of the qualitative method and its hidden potential.
Reading interviews multiple times to get familiar with your data is where most qualitative researchers start. In qualitative research, we immerse ourselves into the study; we do not first start to seek objectivity, but rather closeness. Remember, as a qualitative researcher you are the research tool.
Which method of analyzing to choose?
As a novel researcher, it might be best to stir away from some types of qualitative research methodology and analysis. Grounded theory, for example, might be a bit too complex and ambitious to undertake as your first assignment (if you really want to implement it properly). It might be safer to initially choose a more relaxed way of dealing with your material.
If you have conducted qualitative interviews, here are three methods that can be used to analyze your data:
- Thematic content analysis
This is probably the most common method used in qualitative research. It aims to find common patterns across a data set. It usually follows these steps:
- Getting familiar with the data (reading and re-reading).
- Coding (labeling) the whole text.
- Searching for themes with broader patterns of meaning.
- Reviewing themes to make sure they fit the data.
- Defining and naming themes.
- The write-up (creating a coherent narrative that includes quotes from the interviewees).
- Narrative analysis
This approach is becoming increasingly popular, especially in social sciences. As the name suggests, it is about making sense of stories. It can follow these steps:
- Gather the stories.
- Analyze each story and look for insights and meanings.
- Compare and contrast different stories; look for interpretations.
- Create a new story that connects the previous ones in a novel and insightful way.
- A deductive approach
In some cases, it is possible to use a somewhat non-qualitative approach. Deductive approach means that you already have a predetermined framework for the of analysis. The researcher (you) then uses this framework to analyze the data (i.e. news clippings, transcripts, interviews, etc.) In this approach, the researcher tests his or her pre-existing theories. Themes and concepts are decided before the analysis starts and are imposed on the material. This approach is relatively easy and quick, however, it generally can only be used when you are not seeking depth and new understanding.
Using computer software for data analysis
The good old days when qualitative researchers could be found endlessly rearranging Post-it Notes are probably coming to an end in the near future. Some still prefer the nostalgic pen and paper method of organizing their research material; however, increasing number of researchers now make use of computer programs such as ATLAS.ti or NVivo to help manage their data. This does not mean the computer simply performs the analysis — that is still the job of the researcher. These software programs can nevertheless help us organize, retrieve and present our data in an effective and more coherent way.