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Research Methods | Data Analysis & Statistics

Statistics

Qualitative Data Analysis
       -  General advice
       -  Advanced techniques
       -  Further reading

Statistics

Statistics can be difficult to understand, and the subject is often taught in an uninteresting way. We hope to put that right with a series of bulletins called 'Statistics in Divided Doses' produced by North West Medicines Information in Liverpool. They are written in a relaxed, friendly style and in bitesize chunks for easy digestion.  The bulletins are listed below with a link to the pdf document.

Issue

Subject

Link

1 (2001)

Making observations and taking measurements.

PDF File(132KB)

2 (2001)

Describing a sample.

PDF File(229KB)

3 (2001)

Assessing the reliability of a sample.

PDF File(75KB)

4 (2002)

Variability, Probability and Power.

PDF File(75KB)

5 (2002)

Comparing the Means of Large Samples.

PDF File(145KB)

6 (2003)

Analysing Small Samples: Student's t Test.

PDF File(178KB)

7 (2004)

Non-parametric analysis, Wilcoxon and Mann-Whitney.

PDF File(320KB)

8 (2005)

Confidence intervals.

PDF File(261KB)


Qualitative Data Analysis top of page

There are several theoretical standpoints that qualitative researchers adopt according to their background and the nature of the question to be answered. These include phenomenology, ethnography and grounded theory. They differ in many ways from sampling of participants, to data collection techniques. Depending upon the level you are working at, you may need to discuss and justify your theoretical approach to data analysis (see Further Reading).

General Advice

Despite this, if you are just starting out then there are some common steps to all these qualitative approaches.

Imagine a hypothetical scenario where you wanted to explore and understand the experience of homeopathy and what motivated people to seek such care. You choose to interview 6 purposively selected participants using an in-depth, unstructured approach. The following basic steps could be used to record and analyse your data.

  1. Conduct and audiotape your interview. As you are taping the interview it may help to make written notes as well about aspects of the interaction that the audiotape will not pick up (e.g. facial expressions or gestures). This can help with step number 2, to set the transcript in context.
  2. Transcribe your data into a word processing package; remember that an interview lasting one hour, may take at least 6 hours to transcribe.
  3. Code the data as it is generated. Coding means different things to different researchers but a simple approach would involve looking for similar words or phrases mentioned by the interviewees. These words or phrases are then brought together physically. Either you can photocopy each transcript on different coloured paper (i.e. interviewee 1 on pink, interviewee 2 on yellow etc.) and then cut the relevant phrases from the script using a pair of scissors and arrange them into piles; alternatively you can use the highlighting function in your word processor to highlight the text you’re interested in – again a different colour for each interviewee, and then bring them together in an electronic file. In contrast to some quantitative techniques, data analysis can begin after the first participant has been interviewed, rather than waiting until the end of the study.
  4.  Look for patterns in the data – are there common themes? In this context a theme means a common thread that runs through the data. Themes in your data may keep emerging, but in different forms.
  5. Try to generalise from the themes about the phenomenon in question.
  6. Confront these generalisations with what is already known or through developing a theory.
     

An example of text removed from an interview transcript about the experience of homeopathy is given below:

 ‘You go with specific problems and so often she uncovers other problems, because it deals with everything, not just one problem.  She looks at you as a whole and your body and the mind and everything.  (Interviewee 1)

‘This way you, you know, sat down for an hour an hour and a half, and she actually considered how I was feeling’. (Interviewee 2)

‘Erm, well I went along and erm, when I first got there she gave me…… I suppose what happened was, she talked for quite a while in like the first session, but it was sort of like looking at me as a whole person not just the symptoms of what was wrong with me.  So we talked quite a lot about how I was feeling in myself, just in general, erm, any anxieties, and whether I was having stress and all that sort of thing’. (Interviewee 2)

‘Yes he did the whole things on the same day to find out what the problems were’. (Interviewee 3)

From this data you may try to develop a theme that one of the positive aspects of a homeopathic consultation is the holistic approach to care. This may then allow you to draw generalisations about homeopathic and orthodox care. Finally you may try to develop a hypothesis about why people seek homeopathic care, which could feed into a quantitative study to test this hypothesis.


Advanced Techniques top of page

As discussed above, experienced qualitative researchers will use different theoretical approaches to research, dependent both upon their professional background (e.g. social science, politics etc.) and the nature of the question to be answered. Novice researchers will find the language used by career qualitative researchers inpenetrable and while this section cannot give you in-depth guidance about specific techniques, it will aim to demystify some of the terminology.

The three classic approaches to qualitative research are phenomenology, ethnography and grounded theory.

Phenomenology is used to answer questions about meaning and the essences of an experience. Phenomenology does not generate a theory like some other types of qualitative research, instead it aims to provide insight into how people make sense of the world they live in.

Grounded theory, in contrast, does aim to generate or discover a theory about a particular experience, rather than simply describe the meaning of that experience. For example in the above study exploring why patients seek homeopathic care a phenomenological approach would reveal the individual’s motivation and experience of seeking homeopathic care, whereas a grounded theory model would enable a theory to be developed about what motivates patients to seek such therapy.

Ethnographic studies explore the beliefs and practices of a particular cultural group. It may be used to answer questions such as ‘How is Ayurvedic medicine used with orthodox medicine in Asian patients living with diabetes in Britain?’

With regard to a data analysis strategy within these theoretical approaches, several frameworks exist to assist the researcher (e.g. Colaizzi’s framework in phenomenology). Many are very loosely based around the steps given above. However, some pure qualitative researchers have criticised the development of such frameworks as compromising researchers’ interpretative skills, and trying to adopt the same rigid approach to data analysis as quantitative research. Despite this criticism, these frameworks are useful if you are entering this field as a relative newcomer.

As we are unable to reproduce any of the frameworks here due to copyright, refer to the Further Reading below for more information – Creswell in particular is helpful in setting the scene and directing you towards the relevant references.


Further Reading top of page

Try Pope and Mays first, before Morse and Richards, and then Creswell. Only try Miles and Huberman if you’re serious about qualitative research – we suggest trying to borrow a copy before you consider buying it.

  • Pope C, Mays N, editors. Qualitative research in health care. 2nd ed. London: BMJ; 2000. (The chapters in this book are on the BMJ website for free).


  • Morse JM, Richards L. Read me first for a user’s guide to qualitative research. London: Sage Publications; 2002. (Good for explaining the different theoretical approaches).


  • Creswell JW. Qualitative inquiry and research design – Choosing among the 5 traditions. London: Sage Publications; 1998. (More detailed than Morse and Richards)


  • Miles MB, Huberman AM. Qualitative data analysis. London: Sage Publications; 1994. (Very specialist)
     

MS Word File  This section is also available as a Word download