Articles on the analysis and coding of qualitative data   Qualitative analysis What is qualitative analysis? How do you actually analyse qualitative data? How do you turn the results from your research into findings that can answer your research questions? Analysing qualitative data requires drawing meaning from it... Making the leap from qualitative coding to analysis So you spend weeks or months coding all your qualitative data.

  It’s easy to get seduced by the excitement of primary data collection, and plan your qualitative research around methods that give you rich data from face-to-face contact with participants. But some research questions may be better illustrated or even mostly answered by analysis of existing documents.   This ‘desk-based’ research often doesn’t seem as fun, but can provide a very important wider context that

  Qualitative software used to need you to format text files in very specific ways before they could be imported. These days the software is much more capable and means you can import nearly any kind of text data in any kind of formatting, which allows for a lot more flexibility. However, that easy-going nature can let you get away with some pretty lazy habits. You’ll probably find your analysis (and even data collection and

  Interpretative Phenomenological Analysis (IPA) is an increasingly popular approach to qualitative inquiry and essentially an attempt to understand how participants experience and make meaning of their world. Although not to be confused with the now ubiquitous style of beer with the same initials (India Pale Ale), Interpretative Phenomenological Analysis is similarly accused of being too frequently and imperfectly brewed (Hefferon and

  In the last blog post I referenced a workshop session at the International Conference of Qualitative Inquiry entitled the ‘Archaeology of Coding’. Personally I interpreted archaeology of qualitative analysis as being a process of revisiting and examining an older project. Much of the interpretation in the conference panel was around revisiting and iterating coding within a single analytical attempt, and this is very

  So you spend weeks or months coding all your qualitative data. Maybe you even did it multiple times, using different frameworks and research paradigms. You've followed our introduction guides and everything is neatly (or fairly neatly) organised and inter-related, and you can generate huge reports of all your coding work. Good job! But what happens now?   It's a question asked by lot of qualitative researchers: after all this

The best qualitative research forms an iterative loop, examining, and then re-examining. There are multiple reads of data, multiple layers of coding, and hopefully, constantly improving theory and insight into the underlying lived world. During the research process it is best to try to be in a constant state of feedback with your data, and theory. During your literature review, you may have several cycles through the published literature, with

  Triangles are my favourite shape,   Three points where two lines meet                                                                            alt-J   Qualitative methods are sometimes criticised as being subjective, based on single,

  Since our regular series of articles started nearly three years ago, we have clocked up 100 blog posts on a wide variety of topics in qualitative research and analysis! These are mainly short overviews, aimed at students, newcomers and those looking to refresh their practice. However, they are all referenced with links to full-text academic articles should you need more depth. Some articles also cover practical tips that don't get into

There is a lot more to qualitative coding than just deciding which sections of text belong in which theme. It is a continuing, iterative and often subjective process, which can take weeks or even months. During this time, it’s almost essential to be recording your thoughts, reflecting on the process, and keeping yourself writing and thinking about the bigger picture. Writing doesn’t start after the analysis process, in qualitative

  In the analysis of qualitative data, it can be easy to fall in the habit of creating either very descriptive, or very general theoretical codes. It’s often a good idea to take a step back, and examine your coding framework, challenging yourself to look at the data in a fresh way. There are some more suggestions for how to do this in a blog post article about turning coding strategies on their head. But while in Delhi recently to

To merge or to split qualitative codes, that is the question…   One of the most asked questions when designing a qualitative coding structure is ‘How many codes should I have?’. It’s easy to start out a project thinking that just a few themes will cover the research questions, but sooner or later qualitative analysis tends towards ballooning thematic structure, and before you’ve even started you might have a

For the first time in ages I attended a workshop on qualitative methods, run by the wonderful Johnny Saldaña. Developing software has become a full time (and then some) occupation for me, which means I have little scope for my own professional development as a qualitative researcher. This session was not only a welcome change, but also an eye-opening critique to the way that many in the room (myself included) approach coding

I am really interested in engaging research participants in the research process. While there is an increasing expectation to get ‘lay’ researchers to set research questions, sit on review boards and even ask questions in qualitative studies, it can be more difficult to engage them with the analysis of the research data and this is much rarer in the literature (see Nind 2011). However, Quirkos was specifically designed to make

  When people are doing their first qualitative analysis project using software, it’s difficult to know where to begin. I get a lot of e-mails from people who want some advice in planning out what they will actually DO in the software, and how that will help them. I am happy to help out individually, because everyone’s project is different. However, here are a few pointers which cover the basics and can help demystify the

This week, something completely different! A guest blog from our own Kristin Schroeder!   Most of our blog is a serious and (hopefully) useful exploration of current topics in qualitative research and how to use Quirkos to help you with your research. However we thought it might be fun to share something a little different. I first encountered qualitative research in a serious manner when I joined Quirkos in January this year, and to

  Engaging participants in the research process can be a valuable and insightful endeavour, leading to researchers addressing the right issues, and asking the right questions. Many funding boards in the UK (especially in health) make engaging with members of the public, or targets of the research a requirement in publicly funded research.   While there are similar obligations to provide dissemination and research outputs that are

  We live in a world of deep qualitative data.   It’s often proposed that we are very quantitatively literate. We are exposed to numbers and statistics frequently in news reports, at work, when driving, with fitness apps etc. So we are actually pretty good at understanding things like percentages, fractions, and making sense of them quickly. It’s a good reason why people like to see graphs and numerical summaries of data

  The terms ‘unstructured data’ and ‘qualitative data’ are often used interchangeably, but unstructured data is becoming more commonly associated with data mining and big data approaches to text analytics. Here the comparison is drawn with databases of data where we have a defined field and known value and the loosely structured (especially to a computer) world of language, discussion and comment. A qualitative

Evaluating programmes and projects are an essential part of the feedback loop that should lead to better services. In fact, programmes should be designed with evaluations in mind, to make sure that there are defined and measurable outcomes.   While most evaluations generally include numerical analysis, qualitative data is often used along-side the quantitative, to show richness of project impact, and put a human voice in the process.

When doing analysis and coding in a qualitative research project, it is easy to become completely focused on the thematic framework, and deciding what a section of text is about. However, qualitative analysis software is a useful tool for organising more than just the topics in the text, they can also be used for deeper contextual and meta-level analysis of the coding and data. Because you can pretty much record and categorise anything you

  We are running more and more workshops helping people learn qualitative analysis and Quirkos. I always feel that the best way to learn is by doing, and the best way to remember is through play. To this end, we have created two sources of qualitative data that anyone can download and use (with any package) to learn how to use software for qualitative data analysis.   These can be found at the workshops folder. There are two different

Having been round many market research firms in the last few months, the most striking things is the piles of paper, or at least in the neater offices - shelves of paper! When we talk to small market research firms about their analysis process, many are doing most of their research by printing out data and transcripts, and coding them with coloured highlighters. Some are adamant that this is the way that works best for them, but others are a

There is an interesting new article out, which looks at some of the commonly used algorithms in data mining, and finds that they are generally not very accurate, or even reproducible.   Specifically, the study by Lancichinetti et al. (2015) looks at automated topic classification using the commonly used latent Dirichlet allocation algorithm (LDA), a machine learning process which uses a probabilistic approach to categorise and filter large

Having been to several international conferences on qualitative research recently, there has been a lot of discussion about the future of qualitative research, and the changes happening in the discipline and society as a whole. A lot of people have been saying that acceptance for qualitative research is growing in general: not only are there a large number of well-established specialist journals, but mainstream publications are accepting more

A quick look at the British Library thesis catalogue suggests that around 800 theses are completed every year in the UK using qualitative methods*. This suggests that 7% of the roughly 10,000 annual British PhDs completed use qualitative methods. There are likely to be many more masters theses, and even undergraduate dissertations that use some qualitative methods, so the student demand for qualitative training is considerable.   Usually,

I recently read a great paper by Rettie et al. (2008) which, although based on a small sample size, found that only 9% of UK market research organisations doing qualitative research were using software to help with qualitative analysis.   At first this sounds very low, but it holds true with my own limited experiences with market research firms, and also with academic researchers. The first formal training courses I attended on Qualitative

I'm really happy to see that the talks from the University of Surrey CAQDAS 2014 are now up online (that's 'Computer Assisted Qualitative Data Analysis Software' to you and me). It was a great conference about the current state of software for qualitative analysis, but for me the most interesting talks were from experienced software trainers, about how people actually were using packages in practice. There were many important findings being

In framework analysis, sometimes described as a top-down or 'a-priori' approach, the researcher decides on the topics of interest they will look for before they start the analysis, usually based on a theory they are looking to test. In inductive coding the researcher takes a more bottom-up approach, starting with the data and a blank-sheet, noting themes as the read through the text.   Obviously, many researchers take a pragmatic approach,

In participatory research, we try to get away from the idea of researchers doing research on people, and move to a model where they are conducting research with people.   The movement comes partly from feminist critiques of epistemology, attacking the pervasive notion that knowledge can only be created by experienced academics, The traditional way of doing research generally disempowers people, as the researchers get to decide what