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Qualitative Data Analysis and Interpretation

JN602, Week 11, Veal Chapter 15, CDS Chapter 07

Overlap

Collection and analysis occur simultaneously

Human-as-an-instrument Strength: The researcher can use the results to probe for further information and

detail

and Weakness: Can divert attention away from research objectives

Aims of qualitative analysis

Understand the phenomenon

Go beyond reporting move towards INTERPRETATION

Identify themes and sub-themes

Data storage and confidentialityBecause qualitative data may include personal opinions and details:

Security of data storage is important

Ideally, pseudonyms/codes should be used even with stored data/transcripts etc.

Efforts should be made to protect confidentiality/ anonymity of informants when

reporting results

Structured methods

Use pre-planned questions from structured interview or focus group

Identify common responses within each question

May still have some variety that will need content analysis (unstructured method)

Quantifying methods

Informal methods: identify repetitive or patterned behaviour Frequencies

Content analysis: converting text to numerical variables.

Use coding units - words, themes, items, time

Repertory grid: mental maps

Example - Frequencies

Content analysis

The process of identifying, coding and categorising the primary patterns in the

dataConstant comparative analysis

reads raw data and identifies an important point

Continues reading and identifies another point

Compares to first point and so on

Content analysis process

1. Prepare and organise raw data

2. Source code all raw data

3. Copy raw data

4. Store originals of raw data insafe place

5. Read

6. Theme coding system

7. Compare first theme with

second theme and so on

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8. Data index and classification

(coding frame)

9. Transfer indicated passages to a

file

10. Open coding

11. Axial coding

12. Rules for inclusion

13. Selective coding

14. Mapping

15. Write report

Preparation stages

Prepare and organise raw data transcribe information and audio material

Source code all raw data identify where the information was originally obtained

Example - IA3b4: Interview, with Administrator 3, in the second interview, from

page 4 of the transcript

Copy raw textual data - tends to get marked and destroyed

Store originals of raw data in safe place filing cabinet, locker secure location

required

Read through notes first take, to get overall picture of what you have seen.

Reading + Emergent themes

Reading

The key activity in qualitative data analysis is reading and re-reading the material

Reading begins with initial research questions/models etc. in mind but evolves

Emergent themes

Ideas/concepts which emerge are referred to as emergent themes

For one scenario, see: Fig. 15.2 Initial outline conceptual framework; Fig. 15.3

Annotated interview transcripts; Fig. 15.4 Further developed conceptual

framework

Outline/Initial/Simple conceptual framework

Interview transcript extract annotated Fig. 15.3 (p. 296)Partially developed conceptual framework Fig. 15.4

Mechanics

Annotate transcripts with themes as in Fig. 15.3

Need to leave wide margins or use columns

Colour coding may be helpful

Word-processor may be used to:

Add comments/block text in colour, underline or bold

Search for words/phrases

Code and cross-reference using indexingNumbering paragraphs may be useful for cataloguing

Eg. Career attitude-strategic - Mark: p. 2, para. 3; p. 7, para 4; Jennie: p. 7, para. 1

Steps 6 9 Open coding

First pass through data

Study field notes.

Locate themes, assign initial codes or labels (step 6)

Themes comes from initial question, literature, or from the data.

Similar to a filing system

Aim is to reduce data to manageable categories

Axial coding

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Second pass through data.

Focus on initial coded themes.

Determine consequences, conditions, interactions, processes.

Seek to identify causal patterns in the data

Six Ways to Discover Patterns

Frequencies

Magnitudes

Structures

Processes

Causes

Consequences

Rules for inclusion

Properties or characteristics of passages in the data that identify it as relevant to

that category

i.e. What is included, what is excluded:

May occur at open or axial coding stage

Selective coding

Third/last pass through data.

Involves scanning data and previous codes.

Look for evidence to support themes developed - E.g. text samples

Identify major themes of research, and contrast between themes.

Can involve collapsing themes together (e.g. is there a need for separate categories

of seating)

Unstructured procedure

Convert field notes into written record (reference field notes) Code data to allow storage and retrieval

Write summaries at various stages

Use summaries to construct generalisations to confront existing theories or

construct new theories

Mind mapping

Mind maps were developed in the late 60s by Tony Buzan as a way of helping

students make notes that used only key words and images. They are much quicker to

make, and because of their visual quality much easier to remember and review. The

non-linear nature of mind maps makes it easy to link and cross-reference different

elements of the map. (www.peterussell.com)

Example of mind maps

Lecture: http://www.jcu.edu.au/studying/services/studyskills

/mindmap/samplelecture.html

Website: http://www.peterussell.com/MindMaps/mindmap.php

How to mind map (Russell, 1997)1. Use just key words, or wherever possible images.

2. Start from the center of the page and work out.

3. Make the center a clear and strong visual image that depicts the general theme

of the map.

4. Create sub-centers for sub-themes.

5. Put key words on lines. This reinforces structure of notes.

http://www.jcu.edu.au/studying/services/studyskillshttp://www.jcu.edu.au/studying/services/studyskills

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6. Print rather than write in script. It makes them more readable and memorable.

Lower case is more visually distinctive (and better remembered) than upper

case.

7. Use color to depict themes, associations and to make things stand out.

8. Anything that stands out on the page will stand out in your mind.

9. Think three-dimensionally.10. Use arrows, icons or other visual aids to show links between different

elements.

11. Don't get stuck in one area. If you dry up in one area go to another branch.

12. Put ideas down as they occur, wherever they fit. Don't judge or hold back.

13. Break boundaries. If you run out of space, don't start a new sheet; paste more

paper onto the map. (Break the 8x11 mentality.)

14. Be creative. Creativity aids memory.

15. Get involved. Have fun.

Displaying qualitative data

Often qualitative data can be best represented through visual methods

Matrices: e.g. events flow matrix, effects matrix

Charts and graphs

Mapping: generate conceptual frameworks from themes

Effects matrix

Crosstabulation of qualitative data Fig. 15.5Mapping example CDS Fig.7.8

Using a computer package

Can only assist human judgement - e.g. Nvivo, NUD*IST

The qualitative analysis process

Overlap between gathering and analysis

Manifest vs latent content

Decisions are yours

Gathering data, analysing data and writing report are not mutually exclusive

Need to recognise and account for the role of the researcher in the analysis