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Flashcards in Qualitative research - data analysis Deck (13)
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1

What is the purpose of qualitative data analysis?

-long transcriptions and recorded field notes - data needs to be reduced and have order imposed
1. DESCRIBE
2. DEVELOP THEORY
3. DEVELOP HYPOTHESES - for other research

2

What is meant by 'all data analysis is data reduction'?

-schemes for reducing data - developed during and after data collection
-during = concurrent data analysis
-GT = constant comparative analysis to develop hypotheses + test them out at subsequent interviews

3

How are qualitative data analysed?

-quantification (counting - e.g. count no. of times something is said or individuals contribute)
-Thematic content analysis
-Framework analysis
-Transparent analysis

4

Should qualitative researchers quantify?

-some would say no
-BUT useful for esuring researcher focuses on what is really in the data
-can encourage rigour and honesty
-can be useful to do some quasi (counting) when reporting findings using language such as 'all' 'some' of the PPs said...

5

Challenges for qualitative researchers?

-no rules for data analysis
-no statistical packages to do data analysis for you
-makes qual. data analysis difficult to describe
-have to make sense of loads of data
-interviews often 90 mins
-labour intensive
-presentation = tricky
-if yyou reduce qual. data too much = sense lost and meaningless

6

Transparent analysis?

data analysis does need to be reasonably transparent

7

What are the stages of data analysis?

1. tidy up data
2. check transcription against recording
3. develop method to index the materials so they are easily accessible
4. commonly enter the data into a qualitative data analysis programme e.g. NVivo, Atlas ti - help to organise data and clarify thinking

8

What is thematic content analysis?

-go through transcript looking for themes (things that crop up over and over)
-'commonalities' emerge from data
-themes = given a code (word/phrase)
-codes then collapsed in to categories
-constantly reducing data --> more manageable/meaningful
-looking for variation within data

9

What is framework analysis?

-take a framework to the data and put it into categories
-framework can come from pre-existing theory or initial thematic analysis

10

What happens when data is interrogated?

-do themes apply in certain sub-groups?
e.g. males, mature students
-analysis of negative cases

11

How do researchers check/validate their analyses?

-if more than one researcher - all analyse and then compare
-can also present analyses back to PPs
-member checking - but analysis is interpretive (no right or wrong)

12

What are the final stages of data analysis?

-interelate the themes - so creates an integrated whole/ tells a story
-difficult process - qual. data analysis packages can help e.g. diagramming - but ultimately relies on creativity and intellectual rigour of researcher

13

How is the data presented?

-in a paper - logical journey through the data is presented under a no. of themes
-typically as quotes followed by some analysis

-easier to present qual. findings in a book
-lengthy quotes, followed by clear analysis and interpretation = good way