Qualitative analysis

Qualitative Analysis

Analysing qualitative data

There are several different ways of analysing qualitative data, often reflecting the research method or paradigm that is being used and the researcher's role in the process of data collection. Some forms of enquiry have very specific 'recipes' or ways of conducting data analysis (e.g. phenomenology) and in some data collection and analysis this happen in an iterative fashion (e.g. grounded theory). It is crucial therefore, that the data analysis strategy is congruent with the research approach you have adopted. As we have already noted, the most common data collection methods involve some form of conversation (e.g. interviews, narratives and focus groups), observation (participant, non participant, audio or visual) and/or analysis of documents and texts. This means that you will be mainly dealing with written texts or audio or visual accounts.

iDevice icon Reflection on the recording of non-verbal actions during interviews

How, and why, should you account for the non verbal actions that take place during an interview?

An example of confused meanings, speech and the written text.

"Do you mean that you think you can find out the answer to it?" said the March Hare.
"Exactly so," said Alice.
"Then you should say what you mean," the March Hare went on.
"I do", Alice hastily replied, "at least- at least I mean what I say- that's the same thing you know."
"Not the same thing a bit!" said the Hatter. "You might just as well say that "I see what I eat is the same thing as I eat what I see".

from Lewis Carroll's Alice in Wonderland

When conducting the study, the researcher will have been trying to ascertain something of the experiences, meanings, influences and/or the interpretations of participants. During the analytical stage, the researcher needs to make transparent the paradigm or method used, the impact of any fieldwork roles, what perspectives and influences shaped the way data was collected, and any factors that influenced the participants' response (Kvale's book on interviewing is good for some practical ways of doing this).

Some examples of different qualitative data and suggestions on how to manage these data can be found in these links:

Resource links

Where a research study has an initial proposition (e.g. in grounded theory), then the process of analytic induction may be employed. In these situations, if an interview does not substantiate the initial proposition, then the researcher should consider whether the:

    1. proposition itself needs revision.
    2. sampling has been inadequate
    3. process of data collection requires review.

As the study evolves, you can evaluate the original theoretical ideas with the data emerging. In contrast, with some forms of phenomenology, the analysis does not commence until all the data has been collected. Ethnography uses analytic induction to help the researcher focus on particular issues within the field.

The analytic process can be iterative rather than linear in the attempt to find meaning in the data. This will involve systematically arranging and presenting the data looking for descriptions, contrasts, comparisons and insights. The analysis commences from the first moment the researcher forms a record of the data collected and then decides how to file, organise and retrieve the data.

iDevice icon Reflection on means of filing and retrieving interview data

How might the way interview data were filed and retrieved potentially influence the analysis?

Janesick (2003, p60) outlines some useful rules of thumb for the researcher, consider whether the project demands that you -

  • Look for meaning: -what are the perspectives of the participants in the study?
  • Look for relationships regarding the structure, occurrence and distribution of events over time.
  • Look for points of tension. What does and does not fit and is there any conflicting evidence?

Here are a few guiding points and questions to help manage data;

First of all read the data in its entirety or in manageable sections- gain an overview of the data and make notes of the first impressions.

Focus upon smaller sections in detail.

Does the data say something about types of issues, people or objects?

Looking at the content of the data, can you identify themes, concepts or meanings?

Can you generate codes or categories from the data using these themes, issues, concepts or propositions?

Does your data have anything to say about:

  • events (specific activities, how and what happened, when, why and the consequences).
  • definitions of situations.
  • processes/stages, steps.
  • social structures- behaviours and relationships.
  • strategies- the way people do things?

Where possible, get an independent person to check your analysis. Consider the appropriateness of returning any data to the participants for them to check their responses and your interpretation for accuracy and fairness in representation.

IDevice IconActivity 15: Interview Analysis

Task 1:

Summary

Data analysis can be quite complex and time consuming. The way it is conducted depends upon the research approach guiding the study. The process requires a good audit trail of the influences upon the study and the way the researcher established the rigour, reliability and validity of the research. Data needs revisiting on numerous occasions so that the researcher is literally immersed in the data until no further descriptions, meanings or interpretations can be elicited from the data. Throughout the analysis you will need to ask yourself whether the data are:

  • Sufficient
  • Trustworthy
  • Reliable
  • Valid
  • Generalisable
  • Verified or triangulated
  • Authentic
  • Relevant
  • Representative of the participants and context
You can then make your conclusions!
Now that you have a good general understanding of the principles and practice of qualitative research you can consider what constitutes good qualitative research. Move on to the next section to find out more.