Tag Archives: Qualitative analysis

Qualitative data analysis: data display

20 Oct

The first thing I want to say is that data display was lots of fun!

So my last blog post finished after I had developed and played around with my propositions before moving onto data display.

Miles et al (2014) dedicates 6 chapters to data display (part 2 of their book). I read and re-read these chapters a number of times before I could get my head around everything. Had I not done this, I can see how I may have gone down an inappropriate avenue. Miles et al provide various suggestions along with some smashing examples about how data can be displayed – mainly though matrices and network displays.

For my study, I created matrices (with defined rows and columns). Miles et al describe matric construction as “a creative yet systematic tasks that furthers your understanding of the substance and meaning of your database” (p.113). A key point that resonated with me was that it’s not about building correct matrices – it’s about building ones that will help give answers to the questions you’re asking. To do this, they advise us to “adapt and invest formats that will serve you best” (p.114).

An important conclusion I came to? I didn’t need to use (or fully understand) all the matrices/network displays. I took what I needed to (role-ordered matrices) and combined it with a little of something else (Framework matrices) to allow me to display my data in a way that helped me move on with analysis and progress through to interpretation – always with my research questions at the forefront of my mind (and pinned to my office door).


So here’s what I did: I created a matrix for each main theme (n=4) and each focus group (n=15). In total I created 60 matrices.

My participants were entered along the first row and within each participant cell I also identified key demographic characteristics.  Each subtheme was a column heading. I can’t provide an example of one of my matrices in NVivo as the data is legible, so the image below is a QSR example from their volunteering study.

xxxThe beauty (and massive time saver) of NVivo is that when you click in each cell (number 4 ), the data that you have coded (for the individual within that theme) is displayed on the right of your matrix (number 3). This is referred to as the ‘associated view’. Obviously when you first create your matrix all the cells in the middle will be empty so from the coded data (associated view) a summary needs to be entered into each cell.

For my study, I read through all my coded data and my summaries were developed using the following:

  • Including sufficient detail that was understandable and not overly cryptic
  • Retaining my participants language
  • Sometimes including short verbatim excerpts if I thought it was necessary. All quotes were kept in italics
  • Including my commentaries (in a different colour) about context and focus group interaction

A simple, but important thing I noted when writing my summaries is that not all cells were coded, therefore no summary was required. I always wrote ‘NC’ in those cells so I knew that cells were not empty due to an unintended oversight.

Not surprisingly, as with all stages of data analysis, this process was extremely time consuming. However, by the time I completed it, I had so much more insight into what my data was telling me – for example, the similarities, the differences, the unsurprising and the surprising.  I generally gained a much deeper understanding of what was going on.

However, it didn’t end there. I wanted to compare and contrast my data not only within focus groups, but between focus groups. This I found difficult on a computer screen as I had to jump back and forth across so many matrices.  So….. similar to my propositions, I left my PC and went back to flip chart paper. To be honest, it was a nice break from sitting at my PC.

Another beauty of NVivo is that the matrices can be exported into excel. I did this then transferred them again into a word document (I like prettifying my tables with colours etc. and could only do that the way I wanted in word). It cost me a little more time, but nevertheless, it was worth it. I then printed my matrices out (all 60 of them). For each main theme and subthemes I sellotaped 3 flipchart paper sheets together (so that they were long enough to display all 8 focus groups matrices down both sides) and glued my public focus group matrices down the left hand side and my healthcare professionals’ focus group matrices down the right hand side.

These matrices on the flip chat paper then became my focus for a few weeks. I read them, compared them, returned to the literature, returned to my memos, reflected and took time away to think (long dog walks on the beach helped hugely with this). While I did this, I used the white space in the centre of my flipchart paper (between the matrices) to scribble down my thoughts and concepts. For me, this stage enabled the progression from description to interpretation. I even took them to one of my supervision sessions so I could talk through some of my thoughts and illustrate the process I took to get there. I can show you an image of this as the text is not legible – this is one main theme (with 4 subthemes (column headings (in blue)). The peach rows are my participants:



So in a nut shell, my data display process helped me to get my creative thinking underway for interpretation. I then used these matrices to help me write up my first draft of my findings.

I hope this has been helpful. Qualitative data analysis is so diverse and complex and depends upon a number of variables, particularly your methodological approach so there really is no ‘one size   fits all’. Please do respond to this post and share your experience of the process you took and how it worked for you. Or did you do something similar to me? 🙂

You may have your data, but do you have your data analysis plan?

25 Feb

Fast forward from 28th January (my last blog post) to today – supervision this morning with my data analysis plan in hand. The outcome? I can now get back to my data – nine months after I left it. I really can’t tell you how good that feels!

The development of my qualitative data analysis plan was that last little hurdle I needed to get over before I could return to my data, but it wasn’t straightforward. At times it even felt a little uncomfortable. However, forcing myself to ask very focused and specific questions about my research has enabled me to be pretty damn clear about how I am now going to deal with my data. Backtrack well over nine months ago when I had actually started analysing my data – I had jumped right in with little insight as to what I was looking for and why.

So… after writing my last blog post, I spent some time actually looking for examples of a qualitative analysis plan or even some indication of how to develop one. Despite lots of literature telling me that a data analysis plan is extremely important, I couldn’t actually find evidence of one. I found lots about different analytic strategies/frameworks to use – but this is not an analytic plan. From reading various papers and books and talking to people on twitter, I came up with some key questions that I needed to answer – which subsequently formed my analytical plan:

idea, plan, actionWhat are my research questions? (Extremely important as we know, but I needed to put a lot more thought into them)

What is the overall purpose of my analysis? (If I didn’t know the purpose of my analysis, how was I going to plan how to do it? This linked to my overarching research aim, philosophical and methodological approach in addition to the clinical relevance of my research – the so what question)

How does each of my (large) qualitative data sets connect to my research questions? (I needed to ensure that by analysing my data sets, my research questions could be answered – this was easiest explained as a diagram). This part also made me realise and accept that I have a lot of data that will not feature in my PhD. This is quite ok though as I can use them for future potential publications)

How am I going to conduct the analysis? (The trickiest one for me because I have 4 large (different) data sets, all gained by different methods – yet they are all connected in some way. Further discussion with my supervisors was required for this part. My two options were (1) Will I analyse each data set separately then pull them all together in a discussion? Or (2) Will I analyse them all together and present them in one findings chapter. Considering each option carefully, I listed pros and cons and talked through them in depth with my supervisors. Due to a number of reasons we all agreed on option 2. Within this section, I also had to consider my analytic framework. Again for a number of reasons, Miles and Huberman’s was the winner.

What do I need to ask of my data? (This was also a tricky one because I need to ensure that I have both a deductive and inductive approach to my analysis. I must ensure that I am not ‘blinded’ by my theoretical framework and that it is only there as a scaffold for my analysis. The development of some initial broad propositions helped me with this. This also connects closely with how I am going to conduct my analysis – always keeping my research questions at the forefront of all my decisions).

What resources do I need to conduct my analysis? (This was a simple one – time and patience! Also NVivo – lucky to have a licence with my institution and was fortunate to habe been funded to attend NVivo training).

What is my timeline? (Given all the issues that I have had to address over the last few months, I do not wish to be a slave to the calendar. However, having a rough idea of time is not a bad thing. I am looking at analysing and interpreting for the next 10 months – but who knows! As a part time PhD student, I am extremely fortunate to have a generous amount of protected study leave each year (in addition to a whole semester during the end stages))

So here I have presented important questions that I studied carefully in order to develop my analysis plan. I found this exercise to be extremely beneficial and it also helped my vocalise and rationalise my thoughts and ideas with my supervisors. I am now very excited about finally being able to return to my data, reading my transcripts and listening to my audio recordings (even though I cringe hearing myself ask strange questions, ask 3 questions at once, not letting participants finish, laugh inappropriately, not pick up on a cue, sometimes not make any sense, or just sound ridiculous!)

On a final note, at the end of my analysis plan, I have this – which I like very much:

Lyn Richards (2005) and Bazeley (2009) list five key signs which indicate that the analysis is sufficient:

• Simplicity: a small ‘polished gem of a theory’, rather than a mere pebble of truism
• Elegance and balance: it is coherent
• Completeness: it explains all
• Robustness: it doesn’t fall over with new data
• It makes sense to relevant audiences

Thank you for taking the time to read. Did you develop a similar plan or have you approached this differently. I would be very interested in hearing different/similar approaches so please do leave a comment ….

Qualitative analysis: Where to begin?

16 May

So Monday and Tuesday of this week, following recommendations from one of my supervisors, I atteImagended a qualitative analysis course run by Liz Spencer (one half of Jane Ritchie who developed Framework). I am using Framework for my analysis management with the help of NVivo 9. Details in Chapter 9 of this book (a revised version is being written as we speak).

This course was organised (very well) by the Social Research Association http://www.the-sra.org.uk/sra_scotland.htm

I am now at the stage of having all my qualitative data there (a lot of data!), ready to do something with it! I have spent hours and hours and hours of reading qualitative analysis books and papers and thought I pretty much knew what I had to do. At least in the early stages of analysis anyway. I have also conducted previous qualitative research. Attending this course made me realise that I didn’t know everything and that my previous research has been mainly descriptive. One of my constant niggling worries was moving from the descriptive to the more conceptual stage of analysis and I just couldn’t see how I would be able to do that.

I had high expectations of this course, but it surpassed all my expectations and more. After getting over the star struck feeling of meeting Liz (who is absolutely wonderful by the way and an amazing teacher), I learned more in two days than I think I could ever learn from a text book. One of my main (simple) take home messages was that I cannot get to the conceptual stage and begin proving explanations etc., until I went through all the descriptive stages. This of course takes time and patience. For me, I am now MUCH clearer as to what I need to do at each stage (Liz Spencer’s words – ‘Framework is not an analytic strategy, it is a data management tool to help you work through the process. What we are doing is thematic analysis using this tool’) – a revision I need to make in my methodology chapter!

I am not going to go into any more detail about what I learned here, but what I intend to do is post regular short sharp blogs throughout each stage of my analysis. This I hope will help anyone doing analysis (or about to do analysis). I would also very much welcome comments, questions etc. as it really can help us all learn and develop as we go.


My final piece of advice at this stage would be if the opportunity is available to you, definitely go on one of these courses. I promise you will learn so much…

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