Qualitative Data Analysis Lecture 28 th Recap Transcribing

Qualitative Data Analysis Lecture 28 th

Recap

Transcribing Interviews • Have you thought about how you intend to analyse your data and made sure that your transcription will facilitate this? • Have you chosen clear interviewer and respondent identifiers and used them consistently? • Have you included the interviewer’s questions in full in your transcription? • Have you saved your transcribed data using a separate file for each interview?

Transcribing Interviews • Does your filename maintain confidentiality and preserve anonymity whilst still allowing you to recognize important information easily? • Have you checked your transcript for accuracy and, where necessary, ‘cleaned up’ the data? • Will the package you are going to use help you to manage and analyse your data effectively? In other words, will it do what you need it to do?

Transcribing Interviews • Are your saved transcriptions compatible with the package you intend to use, so you will not lose any features from your word-processed document when you import the data? • Have you checked your transcript for accuracy and ‘cleaned up’ the data prior to importing into your chosen package? • Have you stored a separate back-up or security copy of each data file on your USB mass storage device or burnt one onto a CD? Must do it

Qualitative analysis process • There is no standardized procedure for analysing qualitative data. Despite this, it is still possible to group data into three main types of processes: Summarising (condensation) of meanings; Summarising, therefore, involves condensing the meaning of large amounts of text into fewer words. Categorization (grouping) of meanings; Involves two activities: developing categories and, subsequently, attaching these categories to meaningful chunks of data. Through doing this you will begin to recognize relationships and further develop the categories you are using to facilitate this. Structuring (ordering) of meanings using narrative. Narrative structuring ensures that the data are organised both temporally and with regard to the social or organizational contexts of the research participant (Kvale 1996). This form of analysis focuses upon the stories told during the interviews

Qualitative analysis process • All of these can be used on their own, or in combination, to support interpretation of the data. • Some procedures for analysing qualitative data may be highly structured, whereas others adopt a much lower level of structure. • Related to this, some approaches to analysing qualitative data may be highly formalized such as those associated with categorization. • Whereas others, such as those associated with structuring meanings through narrative, rely much more on the researcher’s interpretation.

Qualitative analysis process Consider the use of analytic aids such as summaries, self memos and a researcher’s diary. Together these processes and aids allow you to interact with your qualitative data in order to: 1) Comprehend them; 2) Integrate related data from transcripts and notes; 3) Identify key themes or patterns for further exploration; 4) Develop and/or test theories based on these patterns; 5) Draw and verify conclusions (Kvale 1996; Miles and Huberman 1994).

Qualitative analysis process • Another pattern matching procedure, which Yin (2003) refers to as a special type, involves an attempt to build an explanation while collecting data and analysing them, rather than testing a predicted explanation as set out above. • Yin (2003) recognizes that this procedure, and labels it “explanation building. ” • Explanation building is designed to test a theoretical proposition. • The explanation-building procedure uses the following stages (Yin 2003):

Qualitative analysis process • Devise a theoretically based proposition, which you will then seek to test. • Undertake data collection through an initial case study in order to be able to compare the findings from this in relation to this theoretically based proposition. • Where necessary, amend theoretically based proposition in the light of the findings from the initial case study. • Undertake a further round of data collection in order to compare the findings from this in relation to the revised proposition.

Qualitative analysis process • Where necessary, further amend the revised proposition in the light of the findings from the second case study. • Undertake further iterations of this process until a satisfactory explanation is derived.

Use of CAQDAS • The use of CAQDAS offers a number of advantages. • When used systematically, it can aid continuity and increase both transparency and methodological rigour. • Despite differences between CAQDAS programs, the basic ways in which they can facilitate your qualitative data analysis are similar. • Lewins and Silver (2006) summarize these as:

Use of CAQDAS Structure of work ability to store or provide connections between all data files within the research project; Closeness to data and interactivity almost instantaneous access to all your data once it has been introduced; Explore the data text search tools enable a word, a phrase or a collection of words to be searched and retrieved within context;

Use of CAQDAS Project management and data organisation powerful means to manage the research project as a whole and organize your data. Data organisation allows you to focus on subsets of data; Writing memos, comments, notes, etc. to record thoughts systematically in relation to the data; Output reports allowing you to view material in hard copy or export it to other applications such as word processors and spreadsheets as well as produce tabular reports.

Summary • Qualitative data are non-numerical data that have not been quantified. They result from the collection of non-standardized data that require classification and are analyzed through the use of conceptualization. • Qualitative analysis generally involves one or more of: Summarising data, categorizing data and structuring data using narrative to recognize relationships, develop and test propositions and produce well-grounded conclusions. It can lead to reanalyzing categories developed from qualitative data quantitatively.

Summary • The processes of data analysis and data collection are necessarily interactive. • There a number of aids that you might use to help you through the process of qualitative analysis, including interim summaries, self-memos and maintaining a researcher’s diary.