Elements of qualitative data analysis Graham R Gibbs

Elements of qualitative data analysis Graham R Gibbs 1 1

Contents v. Books v. Online resources v. Philosophy v. Data preparation v. Coding v. Narrative v. Charts and tables v. CAQDAS 2

Books q Gibbs, G. R. (2007) Analyzing Qualitative Data. London: Sage. q Bernard, H. R. , & Ryan, G. W. (2010). Analyzing qualitative data: Systematic approaches. Los Angeles, [Calif. ]; London: SAGE. q Flick, U. (2009). An introduction to qualitative research. Los Angeles, [Calif. ]; London: SAGE. q Flick, U. (2013). The SAGE handbook of qualitative data analysis. London: SAGE Publications Ltd. q Miles, M. B. , & Huberman, A. M. (1994). Qualitative data analysis: a sourcebook of new methods. Beverly Hills, CA: Sage. The tables in this video are taken from this edition, but there is a new edition: q Miles, M. B. , Huberman, A. M. & Saldaña, J. (2014). Qualitative data analysis: a sourcebook of new methods. 3 rd Ed. Los Angeles, CA: Sage. q Ritchie, J. , Lewis, J. , Mc. Naughton Nicholls, C and Ormston, R (eds) (2013) Qualitative Research Practice: A Guide for Social Science Students and Researchers. London: Sage. 3

Online resources v Online. QDA – http: //onlineqda. hud. ac. uk v My You. Tube Channel – Graham R Gibbs: https: //www. youtube. com/user/Graham. RGibbs v MSc Applied Educational and Social Research @ Strathclyde. – http: //www. strath. ac. uk/aer/materials/ v QSR for NVivo – http: //www. qsrinternational. com/ – NCRM – http: //www. ncrm. ac. uk/ 4

Philosophy v. Realist – Critical Realist – Constructivist – Relativist v. Induction – Deduction - Abduction 5

Data preparation… 6

Transcription: Who should do it? v. Self v. Audio typist v. Dictation/speech recognition software 7

Self v. Tedious but good because it begins data analysis v. Careful reading of whole transcript produces new ideas etc. v. May have no choice if text in a language few others can understand. 8

Software v Dictation/speech recognition software – Still not good enough to transcribe voice from tape or digital recording – Because needs v. good quality sound AND learns your own accent as you use it. – IBM Via Voice or Dragon Dictate – Can listen to tape and then dictate to computer. Still at best only 95% accurate. v Transcription software – E. g. Express Scribe, F 4/F 5 Transribe. 9

Prepare text v. Anonymise – Maybe easier if this is delayed v. Check for accuracy – Member checking (with respondents)? v. Use […] for missing text v. Use [bribery? ] for words you are not sure about. 10

Levels of transcription v People don’t speak in sentences – – Repeat themselves Hesitate, stutter Use contractions (don’t, coz, etc) Use filler words (like, y’know, er, I mean) v Options – – Just the gist Verbatim with dialect Discourse level. 11

Just the gist “ 90% of my communication is with … the Sales Director. 1% of his communication is with me. I try to be one step ahead, I get things ready, … because he jumps from one … project to another. …This morning we did Essex, this afternoon we did BT, and we haven't even finished Essex yet. ”(… indicates omitted speech) 12

Verbatim “I don’t really know. I’ve a feeling that they’re allowed to let their emotions show better. I think bereavement is part of their religion and culture. They tend to be more religious anyway. I’m not from a religious family, so I don’t know that side of it. ” 13

Verbatim with dialect “‘s just that – one o’ staff – they wind everybody up, I mean, – cos I asked for some money – out o’ the safe, cos they only keep money in the safe – ’s our money – so I asked for some money and they wouldn’t give it me – an’ I snatched this tenner what was mine. ” 14

Conversation analysis Bashir: Did you ever (. ) personally assist him with the writing of his book. (0. 8) Princess: A lot of people. hhh ((clears throat)) saw the distress that my life was in. (. ) And they felt it was a supportive thing to help (0. 2) in the way that they did. 15

Start analysis… 16

Coding/indexing/categorizing N. B. confusion because used in quantitative data where it means putting numbers to answers. v“indexing” “categories” “codes” “themes” = linking chunks of data (text) as representative of the same phenomenon. v. Not necessarily to count them (cf. Content analysis) 17

Analysis. Bryman suggests these stages Stage 1 v Read the text as a whole, Make notes at the end v Look for what it is about v Major themes v Unusual issues, events etc v Group cases into types or categories (may reflect research question – e. g. male and female) 18

Stage 2. Read again v. Mark the text (underline, circle, highlight) v. Marginal notes/ annotations v. Labels for codes v. Highlight Key words v. Note any analytic ideas suggested. 19

Stage 3. Code the text v Systematically mark the text v Indicate what chunks of text are about – themes – Index them. v Review the codes. v Eliminate repetition and similar codes (combine) v Think of groupings v May have lots of different codes (Don’t worry at early stage – can be reduced later) 20

Stage 4. Relate general theoretical ideas to the text. v. Coding is only part of analysis v. You must add your interpretation. v. Identify significance for respondents v. Interconnections between codes v. Relation of codes to research question and research literature. 21

Thematic Coding v Grounded Theory (Glaser and Strauss + Corbin + Charmaz) v Interpretative Phenomenological Analysis (Jonathon Smith) v Template analysis (Nigel King) v Framework analysis (Ritchie and Lewis) v All are types of thematic analysis. 22

How is coding done? Text In a village like this. . . the young fellows in the village don't seem to have much difficulty when they're out of work – a fortnight and they're back again – word of mouth, I'd say. It’s a different, tricky situation that I'm in – I just can't say, “Oh, I heard there's a job going on building site, I’ll go and have a go for it. ” I wouldn't be able to do that. Code Age contrast Residence focus Young find work easily Word of mouth Contrast situation Constrained 23

Questions to ask v Look for the gerunds – the doing… v "What is going on? v What are people doing? v What is the person saying? v What do these actions and statements take for granted? v How do structure and context serve to support, maintain, impede or change these actions and statements? " (Charmaz 2003: 94 -95) 24

What can codes be about? Lofland suggests: 1. Acts – usually brief events 2. Activities – of longer duration in a setting, people involved 3. Meanings – what directs participants’ actions? a) What concepts they use to understand their world b) What meaning or significance it has for them. 4. Participation – People’ involvement or adaptation to a setting 5. Relationships – between people, considered simultaneously 6. Settings – the entire context of the events under study 25

What can codes be about? 2 Strauss suggests v Conditions v Interactions v Strategies and tactics v Consequences What happens if… 26

Ways to identify themes Ryan and Bernard (2003) v Repetitions v Indigenous typologies (in vivo) v Metaphors and analogies v Transitions (pauses, sections) v Similarities and Differences – Constant comparison v Linguistic connectors – Because, before, after, next, closeness, examples v Missing data (what is omitted) 27

Coding supports 2 forms of analysis v. Retrieval v. Using the coding frame 28

1. Retrieval v Retrieve all the text coded with the same label = all passages about the same phenomenon, idea, explanation or activity - Literally cut and paste v Used envelopes/files - Now done using software v Enables cross case comparison on same theme. 29

2. Developing the coding frame v. Use the list of codes to examine further kinds of analytic questions, e. g. – relationships between the codes (and the text they code) – Code dimensions – grouping cases 30

Data driven or concept driven? v Inductive or deductive v Most qualitative analysis does both v i. e. start with some theoretical ideas v these derived from literature, research brief/questions, interview schedule v and v discover new ideas, theories, explanations in the data. v Strauss - sociologically constructed codes vs. in vivo codes 31

Description to analytic ‘Dancing’, ‘Indoor bowling’, ‘Dances at works club’, ‘Drive together’ ‘Joint activities ceased’, ‘Joint activities continuing’ ‘Loss of physical co-ordination’, ‘Togetherness’, ‘Doing for’, ‘Resignation’, ‘Core activity’ Descriptive codes Categories Analytic codes 32

Example code hierarchy v Friendship types – Close, generalized – Sporting • Club • Non-club – Work v Changes in Friendship – Making new friends • New same sex friends • New different sex friends – Losing touch – Becoming sexual relationships 33

Example showing analysis v One of a set of interviews by Wendy Hollway and Tony Jefferson. v On fear of crime v Will use some of this for a group work exercise. v Part of interview with: v Barbara 65, F, White, Retired nursing auxiliary, Interview covered, Husband's death, ill health, sister prison, stealing & drug taking, tenants association. From low crime area. 34

INT So you say - well 2 of those things happened after - when you've been talking to this accountant friend of yours. How did it come up? I mean that's er, you'd been alone for quite a while. . BARBARA They'd been burgled. INT Right. BARBARA And they got through a little window like this. Actually 'e'd got a young lad with 'im. And er, Margaret's engagement ring and she says "that was the one thing - that was the one thing, it grieved me more than anything" she said. "They could 'ave the television, the lot" she said. But the fact that they took 'er engagement ring… INT Yeah. BARBARA That upset 'er. And er, we were just talking in general and - and it came up and I says er, "I've got a chain on my door. " And 'e says er, "it's not strong enough that, Barbara. " He says "you really want something else on" and 'e went - his daughter lived up Stokebridge and 'e went to a little shop up there, or something. And got me that chain… 35

BARBARA …And 'e put it on and you can lock it. If you put it on as you're going out, er, its 'ook, and then you 'ave to unlock it to let it drop. INT Ah ha. BARBARA When you come in. INT Oh right. BARBARA You know, you can push the door and it - oh and it is strong as well. INT Ah ha. And the 4 locks on the back? Do they date back further? BARBARA Oh God, yeah. INT So you had lots of security even when your husband was alive? BARBARA Oh yeah, mmm. Mmm. Em, I've got one of those dead locks at the top. INT Yeah. BARBARA You know, they're just a hole in the door and they're not from outside, they're only from inside. And even that locks wrong way. You 'ave to turn it that way to unlock it. (laugh). 36

Notice v. Interviewer and respondent names are in capitals v. Wide margins and space and a half between lines v. Use of contractions v. Place names and people’s names anonymised 37

Read through v. About neighbour being burgled v. Lost TV etc. and engagement ring v. Old and new security on front door. v. Replaced by friend. 38

Mark up text v. Annotations and codes. 39

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Coding Frame v Crime experienced (the type of crime participants discuss having experienced themselves or by their friends and neighbours). – Burglary – Vandalism – Violence v But these descriptive. Be analytic. E. g. – Low level (not reported etc. ) – Significant (with emotional impact) 42

Coding Frame, cont. v Security measures (What measures people have taken to protect themselves, their property etc. both in the past and more recently). – – – – Chain Dead lock Burglar alarm Safe Car alarms Personal Alarm Stay in Walk with others 43

Coding Frame, cont. v. But these descriptive. Be analytic. E. g. – Physical, technology – Behavioural – Psychological (lights on timer etc. ) 44

Coding Frame, cont. v. Feelings about experience of crime – Frightened – Hurt by loss (especially personal items) 45

Descriptive vs Analytic/theoretical v. Descriptive – Just what the people said – What happened – Their terms v. Analytic – Use social science theory – Groups codes together – Use terms the respondents don’t or wouldn’t 46

Narrative… 47

Narrative, Life History and Biography Story and narrative = the way that social actors produce, represent and contexualize their experience and personal knowledge. How they make sense of what happened. v Narrative is the wide, general term. v Story restricted to genre that recounts protagonists, events, complications and consequences. v Data can come from interviews, biography, autobiography, life history interview, personal letters, diaries etc. 48

Three Theorists v Norman Denzin – Narrative as a story of a sequence of events with significance for narrator and audience. – Story has beginning, middle and end a logic. Narratives are temporal = have a causal sequence. v Catherine Kohler Riessman (1993) Elliot Mishler (1986) – During research interviews, respondents often include lengthy stories. 49

Four types of narrative/life history. v. Lieblich et al (1998) Content Form Holistic 1 2 Categorical 3 4 50

1. Holistic content v Looks at complete life story and examines its content. Familiar in clinical case studies. v Use familiar qualitative methods to identify key themes. v Look for transitions between themes v Episodes that seem to contradict themes in terms of content, mood or evaluation by the narrator. v Pay attention to the issues that are not mentioned. 51

Typical themes v Relational story - constantly referring to others. v Belonging and separateness. v Closeness, remoteness and experience of moving. v The meaning of the occupation (e. g vocation) v Relations with opposite sex v Can focus on early life as determinant of later actions. (following Adler) 52

2. Holistic form Looks at the plot or structure of complete life stories. Romance hero faces a series of challenges en route to his goal and eventual victory Comedy goal is the restoration of social order and the hero must have the requisite social skills to overcome the hazards that threaten that order. Tragedy the hero is defeated by the forces of evil and is ostracised from society. Satire a cynical perspective on social hegemony 53

Progression Does story ascend or descend? Climax, turning point (epiphany) etc. v. Advance - story moves to better things v. Regression - story moves to worse things v. Stable - plot is steady, neither worse nor better, just the same. 54

3. Categorical content v. Essentially a content analysis. Extract categories, and count and cross-tabulate. 55

4. Categorical form Discrete linguistic or stylistic linguistic characteristics. Metaphors used, passive vs. active. e. g. use linguistic features to identify inner meaning of events to narrator. v Adverbials like suddenly may indicate how expected or unexpected events were. v Mental verbs like I thought, I understood, and I noticed, may indicate extent to which an experience is in consciousness and can be remembered. 56

4. Categorical form cont. v Denotations of time and place may indicate attempts to distance an event or bring it closer v Past, present and future tense in verbs and transition between them, may indicate a speaker’s sense of identification with the events described. v Transitions between first-person, second-person and thirdperson voice may indicate difficulty of re-encountering a difficult experience. v Passive and active verbs may indicate speaker’s perception of agency. 57

4. Categorical form cont. v Breaking chronological or causal flow with digressions, regressions, leaps in time etc. may indicate attempts to avoid discussion difficult experience. v Repetition may indicate that subject of discussion elicits an emotional charge for narrator. v Detailed description may indicate reluctance to describe difficult emotions. v Method - underline just the words referring to the factual events described. Then examine all the words not underlined. 58

Formal narrative analysis… Use the structure to identify how people tell stories the way they do. v How they give shape to events v How they make a point v How they ‘package’ the narrated events v Their reaction to events v How they articulate their narratives with the audience. 59

Forms and Functions of Stories v A way of passing cultural heritage or organizational culture. – e. g. use of atrocity stories and morality fables in occupational and organizational settings – medical settings use of fables of incompetence gives warnings of what not to do) – Oral culture of schoolchildren - urban legends. v A way of coming to terms with particularly sensitive or traumatic times or events. E. g. divorce or violence. 60

Forms and Functions cont. v. To structure idea of self and self identity. – Psychological view. Stories imitate life and present an inner reality to the outside world. They shape narrator’s identity. The story is one’s identity. We know or discover ourselves and reveal ourselves to others by the stories we tell. v. Show the actor frames and makes sense of a particular set of experiences E. g. – Measures of success – Overcoming adversity – Good and bad practice – Explanations of success or failure 61

Success and moral tales v Collective reminder of what not to do and how not to be. v Common theme = overcoming of difficulties and achievement of success v Challenge –> Adversity –> Success. v + Key turning points (epiphanies) v Can use these as a starting point for further exploration in analysis. 62

Narrative as chronicle. v A form of autobiography. v Actors organize their lives through stories and so make sense of them. v “How it happened” “how I came to be where I am today. ” v e. g. Notion of CAREER v occupational career v other social roles - e. g. parent, children, patients. 63

Diagrams, charts and tables… 64 64

Use for… v Clarification in elicitation process (share with respondents) v Develop ideas about a model, processes etc. v Illustrate examples and your argument v Lay out data so that patterns can be discovered v Data reduction 65

Miles, M. B. and Huberman, A. M. (1994) Qualitative data analysis: a sourcebook of new methods. Beverly Hills, CA: Sage. p. 133 66

Matrices v Simple, like crosstabs. Exclusive values in each cell Or v Non-exclusive values in each cell See: Ritchie, J. and Lewis, J. (eds) (2003) Qualitative Research Practice: A Guide for Social Science Students and Researchers. London: Sage. 67

Character of company departments 68

Summary responses by codes v. Cells contain typical or summaries of text from respondents v. E. g. Job search strategies by gender 69

Job search strategies by gender 70

Example of a comparison within a single case 71

Flow of people through job finding services 72

Miles, M. B. and Huberman, A. M. (1994) Qualitative data analysis: a sourcebook of Slide 73 new methods. Beverly Hills, CA: Sage. p. 225. 73

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CAQDAS v. Computer Assisted Qualitative Data Analysis v. CAQDAS Networking Project – http: //www. surrey. ac. uk/sociology/research/rese archcentres/caqdas/ 75

Current best selling programs v. NVivo v. Atlas. ti v. MAXQDA v. Hyper. RESEARCH v. QDAMiner v. But still small companies cf. Microsoft. – NVivo sold 400, 000, vs Millions for Office 76

Functions v Coding - mark text with code v Retrieve - show all text coded the same way. v Complex retrievals – e. g. text coded with two codes. v Memos v Search (text and codes) & Textual analysis tools v Charts & diagrams v Link with quants data v Relations v Word and pdf documents v Images, video and audio v GIS 77

Debates about CAQDAS v. Distant from data v. Too easy to move to quantify v. Dominance of code and retrieve – Vs narrative thread – Vs postmodern variation v. Fragmentation and decontextualisation v. Coding loses interaction in focus groups v. Needs time and resources to learn 78

Advantage of CAQDAS v. Faster and more efficient v. Helps explanations (eg. Use face sheet data) v. Supports transparency v. Code trees encourage looking at connections v. Avoids anecdotalism - can check frequency 79